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<title>Replication: Jankowski/Rehmert EJPR 2024</title>
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            const clickEl = placeholderDescriptor.dismissOnClick
              ? toggleContainer
              : toggleTitle;

            const closeToggle = () => {
              if (tocShowing) {
                toggleContainer.classList.remove("expanded");
                toggleContents.style.height = "0px";
                tocShowing = false;
              }
            };

            // Get rid of any expanded toggle if the user scrolls
            window.document.addEventListener(
              "scroll",
              throttle(() => {
                closeToggle();
              }, 50)
            );

            // Handle positioning of the toggle
            window.addEventListener(
              "resize",
              throttle(() => {
                elRect = undefined;
                positionToggle();
              }, 50)
            );

            window.addEventListener("quarto-hrChanged", () => {
              elRect = undefined;
            });

            // Process the click
            clickEl.onclick = () => {
              if (!tocShowing) {
                toggleContainer.classList.add("expanded");
                toggleContents.style.height = null;
                tocShowing = true;
              } else {
                closeToggle();
              }
            };
          });
        };

        // Converts a sidebar from a menu back to a sidebar
        const convertToSidebar = () => {
          for (const child of el.children) {
            child.style.opacity = 1;
            child.style.overflow = null;
          }

          const placeholderEl = window.document.getElementById(
            placeholderDescriptor.id
          );
          if (placeholderEl) {
            placeholderEl.remove();
          }

          el.classList.remove("rollup");
        };

        if (isReaderMode()) {
          convertToMenu();
          isVisible = false;
        } else {
          // Find the top and bottom o the element that is being managed
          const elTop = el.offsetTop;
          const elBottom =
            elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;

          if (!isVisible) {
            // If the element is current not visible reveal if there are
            // no conflicts with overlay regions
            if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
              convertToSidebar();
              isVisible = true;
            }
          } else {
            // If the element is visible, hide it if it conflicts with overlay regions
            // and insert a placeholder toggle (or if we're in reader mode)
            if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
              convertToMenu();
              isVisible = false;
            }
          }
        }
      }
    };
  };

  const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]');
  for (const tabEl of tabEls) {
    const id = tabEl.getAttribute("data-bs-target");
    if (id) {
      const columnEl = document.querySelector(
        `${id} .column-margin, .tabset-margin-content`
      );
      if (columnEl)
        tabEl.addEventListener("shown.bs.tab", function (event) {
          const el = event.srcElement;
          if (el) {
            const visibleCls = `${el.id}-margin-content`;
            // walk up until we find a parent tabset
            let panelTabsetEl = el.parentElement;
            while (panelTabsetEl) {
              if (panelTabsetEl.classList.contains("panel-tabset")) {
                break;
              }
              panelTabsetEl = panelTabsetEl.parentElement;
            }

            if (panelTabsetEl) {
              const prevSib = panelTabsetEl.previousElementSibling;
              if (
                prevSib &&
                prevSib.classList.contains("tabset-margin-container")
              ) {
                const childNodes = prevSib.querySelectorAll(
                  ".tabset-margin-content"
                );
                for (const childEl of childNodes) {
                  if (childEl.classList.contains(visibleCls)) {
                    childEl.classList.remove("collapse");
                  } else {
                    childEl.classList.add("collapse");
                  }
                }
              }
            }
          }

          layoutMarginEls();
        });
    }
  }

  // Manage the visibility of the toc and the sidebar
  const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
    id: "quarto-toc-toggle",
    titleSelector: "#toc-title",
    dismissOnClick: true,
  });
  const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
    id: "quarto-sidebarnav-toggle",
    titleSelector: ".title",
    dismissOnClick: false,
  });
  let tocLeftScrollVisibility;
  if (leftTocEl) {
    tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
      id: "quarto-lefttoc-toggle",
      titleSelector: "#toc-title",
      dismissOnClick: true,
    });
  }

  // Find the first element that uses formatting in special columns
  const conflictingEls = window.document.body.querySelectorAll(
    '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
  );

  // Filter all the possibly conflicting elements into ones
  // the do conflict on the left or ride side
  const arrConflictingEls = Array.from(conflictingEls);
  const leftSideConflictEls = arrConflictingEls.filter((el) => {
    if (el.tagName === "ASIDE") {
      return false;
    }
    return Array.from(el.classList).find((className) => {
      return (
        className !== "column-body" &&
        className.startsWith("column-") &&
        !className.endsWith("right") &&
        !className.endsWith("container") &&
        className !== "column-margin"
      );
    });
  });
  const rightSideConflictEls = arrConflictingEls.filter((el) => {
    if (el.tagName === "ASIDE") {
      return true;
    }

    const hasMarginCaption = Array.from(el.classList).find((className) => {
      return className == "margin-caption";
    });
    if (hasMarginCaption) {
      return true;
    }

    return Array.from(el.classList).find((className) => {
      return (
        className !== "column-body" &&
        !className.endsWith("container") &&
        className.startsWith("column-") &&
        !className.endsWith("left")
      );
    });
  });

  const kOverlapPaddingSize = 10;
  function toRegions(els) {
    return els.map((el) => {
      const boundRect = el.getBoundingClientRect();
      const top =
        boundRect.top +
        document.documentElement.scrollTop -
        kOverlapPaddingSize;
      return {
        top,
        bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
      };
    });
  }

  let hasObserved = false;
  const visibleItemObserver = (els) => {
    let visibleElements = [...els];
    const intersectionObserver = new IntersectionObserver(
      (entries, _observer) => {
        entries.forEach((entry) => {
          if (entry.isIntersecting) {
            if (visibleElements.indexOf(entry.target) === -1) {
              visibleElements.push(entry.target);
            }
          } else {
            visibleElements = visibleElements.filter((visibleEntry) => {
              return visibleEntry !== entry;
            });
          }
        });

        if (!hasObserved) {
          hideOverlappedSidebars();
        }
        hasObserved = true;
      },
      {}
    );
    els.forEach((el) => {
      intersectionObserver.observe(el);
    });

    return {
      getVisibleEntries: () => {
        return visibleElements;
      },
    };
  };

  const rightElementObserver = visibleItemObserver(rightSideConflictEls);
  const leftElementObserver = visibleItemObserver(leftSideConflictEls);

  const hideOverlappedSidebars = () => {
    marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries()));
    sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries()));
    if (tocLeftScrollVisibility) {
      tocLeftScrollVisibility(
        toRegions(leftElementObserver.getVisibleEntries())
      );
    }
  };

  window.quartoToggleReader = () => {
    // Applies a slow class (or removes it)
    // to update the transition speed
    const slowTransition = (slow) => {
      const manageTransition = (id, slow) => {
        const el = document.getElementById(id);
        if (el) {
          if (slow) {
            el.classList.add("slow");
          } else {
            el.classList.remove("slow");
          }
        }
      };

      manageTransition("TOC", slow);
      manageTransition("quarto-sidebar", slow);
    };
    const readerMode = !isReaderMode();
    setReaderModeValue(readerMode);

    // If we're entering reader mode, slow the transition
    if (readerMode) {
      slowTransition(readerMode);
    }
    highlightReaderToggle(readerMode);
    hideOverlappedSidebars();

    // If we're exiting reader mode, restore the non-slow transition
    if (!readerMode) {
      slowTransition(!readerMode);
    }
  };

  const highlightReaderToggle = (readerMode) => {
    const els = document.querySelectorAll(".quarto-reader-toggle");
    if (els) {
      els.forEach((el) => {
        if (readerMode) {
          el.classList.add("reader");
        } else {
          el.classList.remove("reader");
        }
      });
    }
  };

  const setReaderModeValue = (val) => {
    if (window.location.protocol !== "file:") {
      window.localStorage.setItem("quarto-reader-mode", val);
    } else {
      localReaderMode = val;
    }
  };

  const isReaderMode = () => {
    if (window.location.protocol !== "file:") {
      return window.localStorage.getItem("quarto-reader-mode") === "true";
    } else {
      return localReaderMode;
    }
  };
  let localReaderMode = null;

  const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded");
  const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1;

  // Walk the TOC and collapse/expand nodes
  // Nodes are expanded if:
  // - they are top level
  // - they have children that are 'active' links
  // - they are directly below an link that is 'active'
  const walk = (el, depth) => {
    // Tick depth when we enter a UL
    if (el.tagName === "UL") {
      depth = depth + 1;
    }

    // It this is active link
    let isActiveNode = false;
    if (el.tagName === "A" && el.classList.contains("active")) {
      isActiveNode = true;
    }

    // See if there is an active child to this element
    let hasActiveChild = false;
    for (child of el.children) {
      hasActiveChild = walk(child, depth) || hasActiveChild;
    }

    // Process the collapse state if this is an UL
    if (el.tagName === "UL") {
      if (tocOpenDepth === -1 && depth > 1) {
        el.classList.add("collapse");
      } else if (
        depth <= tocOpenDepth ||
        hasActiveChild ||
        prevSiblingIsActiveLink(el)
      ) {
        el.classList.remove("collapse");
      } else {
        el.classList.add("collapse");
      }

      // untick depth when we leave a UL
      depth = depth - 1;
    }
    return hasActiveChild || isActiveNode;
  };

  // walk the TOC and expand / collapse any items that should be shown

  if (tocEl) {
    walk(tocEl, 0);
    updateActiveLink();
  }

  // Throttle the scroll event and walk peridiocally
  window.document.addEventListener(
    "scroll",
    throttle(() => {
      if (tocEl) {
        updateActiveLink();
        walk(tocEl, 0);
      }
      if (!isReaderMode()) {
        hideOverlappedSidebars();
      }
    }, 5)
  );
  window.addEventListener(
    "resize",
    throttle(() => {
      if (!isReaderMode()) {
        hideOverlappedSidebars();
      }
    }, 10)
  );
  hideOverlappedSidebars();
  highlightReaderToggle(isReaderMode());
});

// grouped tabsets
window.addEventListener("pageshow", (_event) => {
  function getTabSettings() {
    const data = localStorage.getItem("quarto-persistent-tabsets-data");
    if (!data) {
      localStorage.setItem("quarto-persistent-tabsets-data", "{}");
      return {};
    }
    if (data) {
      return JSON.parse(data);
    }
  }

  function setTabSettings(data) {
    localStorage.setItem(
      "quarto-persistent-tabsets-data",
      JSON.stringify(data)
    );
  }

  function setTabState(groupName, groupValue) {
    const data = getTabSettings();
    data[groupName] = groupValue;
    setTabSettings(data);
  }

  function toggleTab(tab, active) {
    const tabPanelId = tab.getAttribute("aria-controls");
    const tabPanel = document.getElementById(tabPanelId);
    if (active) {
      tab.classList.add("active");
      tabPanel.classList.add("active");
    } else {
      tab.classList.remove("active");
      tabPanel.classList.remove("active");
    }
  }

  function toggleAll(selectedGroup, selectorsToSync) {
    for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) {
      const active = selectedGroup === thisGroup;
      for (const tab of tabs) {
        toggleTab(tab, active);
      }
    }
  }

  function findSelectorsToSyncByLanguage() {
    const result = {};
    const tabs = Array.from(
      document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
    );
    for (const item of tabs) {
      const div = item.parentElement.parentElement.parentElement;
      const group = div.getAttribute("data-group");
      if (!result[group]) {
        result[group] = {};
      }
      const selectorsToSync = result[group];
      const value = item.innerHTML;
      if (!selectorsToSync[value]) {
        selectorsToSync[value] = [];
      }
      selectorsToSync[value].push(item);
    }
    return result;
  }

  function setupSelectorSync() {
    const selectorsToSync = findSelectorsToSyncByLanguage();
    Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => {
      Object.entries(tabSetsByValue).forEach(([value, items]) => {
        items.forEach((item) => {
          item.addEventListener("click", (_event) => {
            setTabState(group, value);
            toggleAll(value, selectorsToSync[group]);
          });
        });
      });
    });
    return selectorsToSync;
  }

  const selectorsToSync = setupSelectorSync();
  for (const [group, selectedName] of Object.entries(getTabSettings())) {
    const selectors = selectorsToSync[group];
    // it's possible that stale state gives us empty selections, so we explicitly check here.
    if (selectors) {
      toggleAll(selectedName, selectors);
    }
  }
});

function throttle(func, wait) {
  let waiting = false;
  return function () {
    if (!waiting) {
      func.apply(this, arguments);
      waiting = true;
      setTimeout(function () {
        waiting = false;
      }, wait);
    }
  };
}

function nexttick(func) {
  return setTimeout(func, 0);
}
</script>
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s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;i<t;i++)e[i]=arguments[i];return!e.some((function(t){return!(t&&"function"==typeof t.getBoundingClientRect)}))}function mi(t){void 0===t&&(t={});var e=t,i=e.defaultModifiers,n=void 0===i?[]:i,s=e.defaultOptions,o=void 0===s?fi:s;return function(t,e,i){void 0===i&&(i=o);var s,r,a={placement:"bottom",orderedModifiers:[],options:Object.assign({},fi,o),modifiersData:{},elements:{reference:t,popper:e},attributes:{},styles:{}},l=[],c=!1,h={state:a,setOptions:function(i){var s="function"==typeof 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vi=Object.freeze(Object.defineProperty({__proto__:null,afterMain:ae,afterRead:se,afterWrite:he,applyStyles:_e,arrow:je,auto:Kt,basePlacements:Qt,beforeMain:oe,beforeRead:ie,beforeWrite:le,bottom:Rt,clippingParents:Ut,computeStyles:Be,createPopper:bi,createPopperBase:gi,createPopperLite:_i,detectOverflow:ii,end:Yt,eventListeners:Re,flip:si,hide:ai,left:Vt,main:re,modifierPhases:de,offset:li,placements:ee,popper:Jt,popperGenerator:mi,popperOffsets:ci,preventOverflow:hi,read:ne,reference:Zt,right:qt,start:Xt,top:zt,variationPlacements:te,viewport:Gt,write:ce},Symbol.toStringTag,{value:"Module"})),yi="dropdown",wi=".bs.dropdown",Ai=".data-api",Ei="ArrowUp",Ti="ArrowDown",Ci=`hide${wi}`,Oi=`hidden${wi}`,xi=`show${wi}`,ki=`shown${wi}`,Li=`click${wi}${Ai}`,Si=`keydown${wi}${Ai}`,Di=`keyup${wi}${Ai}`,$i="show",Ii='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',Ni=`${Ii}.${$i}`,Pi=".dropdown-menu",Mi=p()?"top-end":"top-start",ji=p()?"top-start":"top-end",Fi=p()?"bottom-end":"bottom-start",Hi=p()?"bottom-start":"bottom-end",Wi=p()?"left-start":"right-start",Bi=p()?"right-start":"left-start",zi={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},Ri={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class qi extends W{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=z.next(this._element,Pi)[0]||z.prev(this._element,Pi)[0]||z.findOne(Pi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return zi}static get DefaultType(){return Ri}static get NAME(){return yi}toggle(){return this._isShown()?this.hide():this.show()}show(){if(l(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!N.trigger(this._element,xi,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add($i),this._element.classList.add($i),N.trigger(this._element,ki,t)}}hide(){if(l(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!N.trigger(this._element,Ci,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._popper&&this._popper.destroy(),this._menu.classList.remove($i),this._element.classList.remove($i),this._element.setAttribute("aria-expanded","false"),F.removeDataAttribute(this._menu,"popper"),N.trigger(this._element,Oi,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${yi.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===vi)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:o(this._config.reference)?t=r(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const e=this._getPopperConfig();this._popper=bi(t,this._menu,e)}_isShown(){return this._menu.classList.contains($i)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Wi;if(t.classList.contains("dropstart"))return Bi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ji:Mi:e?Hi:Fi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>a(t)));i.length&&b(i,e,t===Ti,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=qi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=z.find(Ni);for(const i of e){const e=qi.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"<div></div>"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return 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) format("woff");
}
.bi::before,
[class^="bi-"]::before,
[class*=" bi-"]::before {
display: inline-block;
font-family: bootstrap-icons !important;
font-style: normal;
font-weight: normal !important;
font-variant: normal;
text-transform: none;
line-height: 1;
vertical-align: -.125em;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
.bi-123::before { content: "\f67f"; }
.bi-alarm-fill::before { content: "\f101"; }
.bi-alarm::before { content: "\f102"; }
.bi-align-bottom::before { content: "\f103"; }
.bi-align-center::before { content: "\f104"; }
.bi-align-end::before { content: "\f105"; }
.bi-align-middle::before { content: "\f106"; }
.bi-align-start::before { content: "\f107"; }
.bi-align-top::before { content: "\f108"; }
.bi-alt::before { content: "\f109"; }
.bi-app-indicator::before { content: "\f10a"; }
.bi-app::before { content: "\f10b"; }
.bi-archive-fill::before { content: "\f10c"; }
.bi-archive::before { content: "\f10d"; }
.bi-arrow-90deg-down::before { content: "\f10e"; }
.bi-arrow-90deg-left::before { content: "\f10f"; }
.bi-arrow-90deg-right::before { content: "\f110"; }
.bi-arrow-90deg-up::before { content: "\f111"; }
.bi-arrow-bar-down::before { content: "\f112"; }
.bi-arrow-bar-left::before { content: "\f113"; }
.bi-arrow-bar-right::before { content: "\f114"; }
.bi-arrow-bar-up::before { content: "\f115"; }
.bi-arrow-clockwise::before { content: "\f116"; }
.bi-arrow-counterclockwise::before { content: "\f117"; }
.bi-arrow-down-circle-fill::before { content: "\f118"; }
.bi-arrow-down-circle::before { content: "\f119"; }
.bi-arrow-down-left-circle-fill::before { content: "\f11a"; }
.bi-arrow-down-left-circle::before { content: "\f11b"; }
.bi-arrow-down-left-square-fill::before { content: "\f11c"; }
.bi-arrow-down-left-square::before { content: "\f11d"; }
.bi-arrow-down-left::before { content: "\f11e"; }
.bi-arrow-down-right-circle-fill::before { content: "\f11f"; }
.bi-arrow-down-right-circle::before { content: "\f120"; }
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.bi-suitcase-fill::before { content: "\f8fd"; }
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.bi-suitcase2-fill::before { content: "\f901"; }
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.bi-vignette::before { content: "\f903"; }
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  <nav id="TOC" role="doc-toc" class="toc-active">
    <h2 id="toc-title">Content</h2>
   
  <ul>
  <li><a href="#about" id="toc-about" class="nav-link active" data-scroll-target="#about"><span class="header-section-number">1</span> About</a></li>
  <li><a href="#packages-and-data" id="toc-packages-and-data" class="nav-link" data-scroll-target="#packages-and-data"><span class="header-section-number">2</span> Packages and Data</a></li>
  <li><a href="#table-1" id="toc-table-1" class="nav-link" data-scroll-target="#table-1"><span class="header-section-number">3</span> Table 1</a></li>
  <li><a href="#table-2" id="toc-table-2" class="nav-link" data-scroll-target="#table-2"><span class="header-section-number">4</span> Table 2</a></li>
  <li><a href="#figure-1-figure-2-figure-3-figure-a22-figure-a23" id="toc-figure-1-figure-2-figure-3-figure-a22-figure-a23" class="nav-link" data-scroll-target="#figure-1-figure-2-figure-3-figure-a22-figure-a23"><span class="header-section-number">5</span> Figure 1, Figure 2, Figure 3, Figure A22, Figure A23</a></li>
  <li><a href="#table-m" id="toc-table-m" class="nav-link" data-scroll-target="#table-m"><span class="header-section-number">6</span> TABLE M</a></li>
  <li><a href="#fri-figure-a8-figure-4-table-3-table-a3-figure-a4" id="toc-fri-figure-a8-figure-4-table-3-table-a3-figure-a4" class="nav-link" data-scroll-target="#fri-figure-a8-figure-4-table-3-table-a3-figure-a4"><span class="header-section-number">7</span> FRI: FIGURE A8, FIGURE 4, TABLE 3, TABLE A3, FIGURE A4</a></li>
  <li><a href="#zipper-figure-5-appendix-g-table-4" id="toc-zipper-figure-5-appendix-g-table-4" class="nav-link" data-scroll-target="#zipper-figure-5-appendix-g-table-4"><span class="header-section-number">8</span> ZIPPER: FIGURE 5 + APPENDIX G + TABLE 4</a></li>
  <li><a href="#appendix-c" id="toc-appendix-c" class="nav-link" data-scroll-target="#appendix-c"><span class="header-section-number">9</span> Appendix C</a></li>
  <li><a href="#appendix-d" id="toc-appendix-d" class="nav-link" data-scroll-target="#appendix-d"><span class="header-section-number">10</span> Appendix D</a></li>
  <li><a href="#appendix-e" id="toc-appendix-e" class="nav-link" data-scroll-target="#appendix-e"><span class="header-section-number">11</span> Appendix E</a></li>
  <li><a href="#appendix-k" id="toc-appendix-k" class="nav-link" data-scroll-target="#appendix-k"><span class="header-section-number">12</span> Appendix K</a></li>
  <li><a href="#appendix-k-1" id="toc-appendix-k-1" class="nav-link" data-scroll-target="#appendix-k-1"><span class="header-section-number">13</span> Appendix K</a></li>
  <li><a href="#session-info" id="toc-session-info" class="nav-link" data-scroll-target="#session-info"><span class="header-section-number">14</span> Session info</a></li>
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<header id="title-block-header" class="quarto-title-block default">
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<h1 class="title">Replication: Jankowski/Rehmert EJPR 2024</h1>
</div>



<div class="quarto-title-meta">

    <div>
    <div class="quarto-title-meta-heading">Authors</div>
    <div class="quarto-title-meta-contents">
             <p>Michael Jankowski </p>
             <p>Jochen Rehmert </p>
          </div>
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    <div>
    <div class="quarto-title-meta-heading">Published</div>
    <div class="quarto-title-meta-contents">
      <p class="date">08 August, 2025</p>
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</header>


<section id="about" class="level2" data-number="1">
<h2 data-number="1" class="anchored" data-anchor-id="about"><span class="header-section-number">1</span> About</h2>
<p>This quarto document provides all code for replicating the paper:</p>
<p>Jankowski, Michael &amp; Jochen Rehmert. 2024. Ranking and Selecting Women under PR: Evidence from a Two-Stage Conjoint Experiment. <em>European Journal of Political Research</em>. (currently, as of preparing this replication data, only accepted, so no DOI).</p>
<p>The data comes with the replication zip-file. The data is preprocessed and should not contain any information to identify the respondents. We have scripts which take the original Qualtrics survey file and transform the data in the final format used for the analysis. The replication data contains lots of additional variables which were used while programming the experiment, but which are of no relevance for the analysis.</p>
<p>To run the replication follow these steps:</p>
<ol type="1">
<li>Install R and R Studio.</li>
<li>Open the RStudio project that comes with the zip file.</li>
<li>Open the .qmd file.</li>
<li>Run the different cells to replicate the respective tables and figures.</li>
</ol>
<p>In case of any questions, please contact Michael: michael.jankowski@uol.de</p>
<p>The code was last run using R 4.4.1. At the end of the file a full description is provided.</p>
</section>
<section id="packages-and-data" class="level2" data-number="2">
<h2 data-number="2" class="anchored" data-anchor-id="packages-and-data"><span class="header-section-number">2</span> Packages and Data</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (&lt;http://conflicted.r-lib.org/&gt;) to force all conflicts to become errors</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(cjoint)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Lade nötiges Paket: sandwich
Lade nötiges Paket: lmtest
Lade nötiges Paket: zoo

Attache Paket: &#39;zoo&#39;

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    as.Date, as.Date.numeric

Lade nötiges Paket: survey
Lade nötiges Paket: grid
Lade nötiges Paket: Matrix

Attache Paket: &#39;Matrix&#39;

Die folgenden Objekte sind maskiert von &#39;package:tidyr&#39;:

    expand, pack, unpack

Lade nötiges Paket: survival

Attache Paket: &#39;survey&#39;

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    dotchart

cjoint: AMCE Estimator for Conjoint Experiments
Version: 2.1.1
Authors: Soubhik Barari, Elissa Berwick, Jens Hainmueller, Daniel Hopkins, Sean Liu, Anton Strezhnev, Teppei Yamamoto


Attache Paket: &#39;cjoint&#39;

Das folgende Objekt ist maskiert &#39;package:tibble&#39;:

    view</code></pre>
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<summary>Code</summary>
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(rvest)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<pre><code>
Attache Paket: &#39;rvest&#39;

Das folgende Objekt ist maskiert &#39;package:readr&#39;:

    guess_encoding</code></pre>
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<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(haven)</span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(cregg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<pre><code>
Attache Paket: &#39;cregg&#39;

Das folgende Objekt ist maskiert &#39;package:cjoint&#39;:

    amce</code></pre>
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<summary>Code</summary>
<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(margins)</span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(MNLpred)</span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(nnet) </span>
<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(MASS) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<pre><code>
Attache Paket: &#39;MASS&#39;

Das folgende Objekt ist maskiert &#39;package:dplyr&#39;:

    select</code></pre>
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<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(scales)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<pre><code>
Attache Paket: &#39;scales&#39;

Das folgende Objekt ist maskiert &#39;package:purrr&#39;:

    discard

Das folgende Objekt ist maskiert &#39;package:readr&#39;:

    col_factor</code></pre>
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<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggh4x)</span>
<span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(data.table)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stderr">
<pre><code>
Attache Paket: &#39;data.table&#39;

Die folgenden Objekte sind maskiert von &#39;package:zoo&#39;:

    yearmon, yearqtr

Die folgenden Objekte sind maskiert von &#39;package:lubridate&#39;:

    hour, isoweek, mday, minute, month, quarter, second, wday, week,
    yday, year

Die folgenden Objekte sind maskiert von &#39;package:dplyr&#39;:

    between, first, last

Das folgende Objekt ist maskiert &#39;package:purrr&#39;:

    transpose</code></pre>
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<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb15"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(fastDummies)</span>
<span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(rio)</span>
<span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(texreg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<pre><code>Version:  1.39.3
Date:     2023-11-09
Author:   Philip Leifeld (University of Essex)

Consider submitting praise using the praise or praise_interactive functions.
Please cite the JSS article in your publications -- see citation(&quot;texreg&quot;).

Attache Paket: &#39;texreg&#39;

Das folgende Objekt ist maskiert &#39;package:tidyr&#39;:

    extract</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb17"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a>respondents <span class="ot">&lt;-</span> rio<span class="sc">::</span><span class="fu">import</span>(<span class="st">&quot;respondents.csv&quot;</span>)</span>
<span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span> <span class="fu">readRDS</span>(<span class="st">&quot;long_data_prep.rds&quot;</span>)</span>
<span id="cb17-4"><a href="#cb17-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb17-5"><a href="#cb17-5" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb17-6"><a href="#cb17-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb17-7"><a href="#cb17-7" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span></span>
<span id="cb17-8"><a href="#cb17-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(ResponseID) <span class="sc">%&gt;%</span></span>
<span id="cb17-9"><a href="#cb17-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">n_women =</span> <span class="fu">sum</span>(fct_gender <span class="sc">==</span> <span class="st">&quot;Female&quot;</span>)) <span class="ot">-&gt;</span> df</span>
<span id="cb17-10"><a href="#cb17-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb17-11"><a href="#cb17-11" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>respondent_party <span class="ot">&lt;-</span> <span class="fu">case_when</span>(df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;Gruene&quot;</span> <span class="sc">~</span> <span class="dv">1</span>,</span>
<span id="cb17-12"><a href="#cb17-12" aria-hidden="true" tabindex="-1"></a>                                 df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;NEOS&quot;</span> <span class="sc">~</span> <span class="dv">2</span>,</span>
<span id="cb17-13"><a href="#cb17-13" aria-hidden="true" tabindex="-1"></a>                                 df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;SPO&quot;</span> <span class="sc">~</span> <span class="dv">3</span>,</span>
<span id="cb17-14"><a href="#cb17-14" aria-hidden="true" tabindex="-1"></a>                                 df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;OVP&quot;</span> <span class="sc">~</span> <span class="dv">4</span>,</span>
<span id="cb17-15"><a href="#cb17-15" aria-hidden="true" tabindex="-1"></a>                                 df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;FPO&quot;</span> <span class="sc">~</span> <span class="dv">5</span>) <span class="sc">%&gt;%</span></span>
<span id="cb17-16"><a href="#cb17-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">factor</span>(<span class="at">levels =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">5</span>, <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">&quot;Greens&quot;</span>, <span class="st">&quot;NEOS&quot;</span>, <span class="st">&quot;SPÖ&quot;</span>, <span class="st">&quot;ÖVP&quot;</span>, <span class="st">&quot;FPÖ&quot;</span>))</span>
<span id="cb17-17"><a href="#cb17-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb17-18"><a href="#cb17-18" aria-hidden="true" tabindex="-1"></a>vorstand <span class="ot">&lt;-</span> data.table<span class="sc">::</span><span class="fu">fread</span>(<span class="st">&quot;vorstände_austria.csv&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
</section>
<section id="table-1" class="level2" data-number="3">
<h2 data-number="3" class="anchored" data-anchor-id="table-1"><span class="header-section-number">3</span> Table 1</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="co"># full party information</span></span>
<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a><span class="fu">table</span>(vorstand<span class="sc">$</span>Party) <span class="co"># N Total</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stdout">
<pre><code>
   SP\xd6    \xd6VP      NEOS GR\xdcNEN    FP\xd6 
     1058      1080       411       804       402 </code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a><span class="fu">table</span>(vorstand<span class="sc">$</span>Anrede1) <span class="co"># N Gender (mentioned in text)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stdout">
<pre><code>
 Sehr geehrte Frau Sehr geehrter Herr 
              1309               2446 </code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb22"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb22-1"><a href="#cb22-1" aria-hidden="true" tabindex="-1"></a>respondents <span class="sc">%&gt;%</span> </span>
<span id="cb22-2"><a href="#cb22-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(party) <span class="sc">%&gt;%</span> </span>
<span id="cb22-3"><a href="#cb22-3" aria-hidden="true" tabindex="-1"></a>  count <span class="sc">%&gt;%</span></span>
<span id="cb22-4"><a href="#cb22-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb22-5"><a href="#cb22-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 5 × 3
  party      n percent
  &lt;chr&gt;  &lt;int&gt;   &lt;dbl&gt;
1 FPO       19    5.86
2 Gruene   121   37.3 
3 NEOS      40   12.3 
4 OVP       56   17.3 
5 SPO       88   27.2 </code></pre>
</div>
</div>
</section>
<section id="table-2" class="level2" data-number="4">
<h2 data-number="4" class="anchored" data-anchor-id="table-2"><span class="header-section-number">4</span> Table 2</h2>
<p>We created it manually, so no code.</p>
</section>
<section id="figure-1-figure-2-figure-3-figure-a22-figure-a23" class="level2" data-number="5">
<h2 data-number="5" class="anchored" data-anchor-id="figure-1-figure-2-figure-3-figure-a22-figure-a23"><span class="header-section-number">5</span> Figure 1, Figure 2, Figure 3, Figure A22, Figure A23</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb24"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1" aria-hidden="true" tabindex="-1"></a><span class="do">######################################################</span></span>
<span id="cb24-2"><a href="#cb24-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Probability of Gender on ballot position/selection</span></span>
<span id="cb24-3"><a href="#cb24-3" aria-hidden="true" tabindex="-1"></a><span class="do">######################################################</span></span>
<span id="cb24-4"><a href="#cb24-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-5"><a href="#cb24-5" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(df<span class="sc">$</span>ballotposition), </span>
<span id="cb24-6"><a href="#cb24-6" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb24-7"><a href="#cb24-7" aria-hidden="true" tabindex="-1"></a>                                df<span class="sc">$</span>ballotposition)</span>
<span id="cb24-8"><a href="#cb24-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-9"><a href="#cb24-9" aria-hidden="true" tabindex="-1"></a><span class="co"># multinomial predcition packages need dummy variables...</span></span>
<span id="cb24-10"><a href="#cb24-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-11"><a href="#cb24-11" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-12"><a href="#cb24-12" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_gender&quot;</span>,</span>
<span id="cb24-13"><a href="#cb24-13" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-14"><a href="#cb24-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-15"><a href="#cb24-15" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-16"><a href="#cb24-16" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_age&quot;</span>,</span>
<span id="cb24-17"><a href="#cb24-17" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-18"><a href="#cb24-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-19"><a href="#cb24-19" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-20"><a href="#cb24-20" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_deviation&quot;</span>,</span>
<span id="cb24-21"><a href="#cb24-21" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-22"><a href="#cb24-22" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-23"><a href="#cb24-23" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-24"><a href="#cb24-24" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_experience&quot;</span>,</span>
<span id="cb24-25"><a href="#cb24-25" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-26"><a href="#cb24-26" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-27"><a href="#cb24-27" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-28"><a href="#cb24-28" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_position&quot;</span>,</span>
<span id="cb24-29"><a href="#cb24-29" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-30"><a href="#cb24-30" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-31"><a href="#cb24-31" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-32"><a href="#cb24-32" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_issue&quot;</span>,</span>
<span id="cb24-33"><a href="#cb24-33" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-34"><a href="#cb24-34" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-35"><a href="#cb24-35" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-36"><a href="#cb24-36" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_otherlist&quot;</span>,</span>
<span id="cb24-37"><a href="#cb24-37" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-38"><a href="#cb24-38" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-39"><a href="#cb24-39" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span>  fastDummies<span class="sc">::</span><span class="fu">dummy_cols</span>(df, </span>
<span id="cb24-40"><a href="#cb24-40" aria-hidden="true" tabindex="-1"></a>                               <span class="at">select_columns =</span> <span class="st">&quot;fct_personalvotes&quot;</span>,</span>
<span id="cb24-41"><a href="#cb24-41" aria-hidden="true" tabindex="-1"></a>                               <span class="at">remove_first_dummy =</span> <span class="cn">TRUE</span>)</span>
<span id="cb24-42"><a href="#cb24-42" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-43"><a href="#cb24-43" aria-hidden="true" tabindex="-1"></a><span class="fu">names</span>(df) <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;-|/&quot;</span>, <span class="st">&quot;&quot;</span>, <span class="fu">names</span>(df))</span>
<span id="cb24-44"><a href="#cb24-44" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-45"><a href="#cb24-45" aria-hidden="true" tabindex="-1"></a><span class="co"># formulas for differen regression models</span></span>
<span id="cb24-46"><a href="#cb24-46" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-47"><a href="#cb24-47" aria-hidden="true" tabindex="-1"></a>f0 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))] </span>
<span id="cb24-48"><a href="#cb24-48" aria-hidden="true" tabindex="-1"></a>f0 <span class="ot">&lt;-</span> f0[f0 <span class="sc">!=</span> <span class="st">&quot;fct_gender_Male&quot;</span>]</span>
<span id="cb24-49"><a href="#cb24-49" aria-hidden="true" tabindex="-1"></a>f0 <span class="ot">&lt;-</span> <span class="fu">paste</span>(f0, <span class="at">collapse =</span> <span class="st">&quot; + &quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb24-50"><a href="#cb24-50" aria-hidden="true" tabindex="-1"></a>  <span class="fu">paste</span>(<span class="st">&quot;ballotposition_new ~ fct_gender_Male +&quot;</span>, .)</span>
<span id="cb24-51"><a href="#cb24-51" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-52"><a href="#cb24-52" aria-hidden="true" tabindex="-1"></a>f1 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))] </span>
<span id="cb24-53"><a href="#cb24-53" aria-hidden="true" tabindex="-1"></a>f1 <span class="ot">&lt;-</span> f1[f1 <span class="sc">!=</span> <span class="st">&quot;fct_gender_Male&quot;</span>]</span>
<span id="cb24-54"><a href="#cb24-54" aria-hidden="true" tabindex="-1"></a>f1 <span class="ot">&lt;-</span> <span class="fu">paste</span>(f1, <span class="at">collapse =</span> <span class="st">&quot; + &quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb24-55"><a href="#cb24-55" aria-hidden="true" tabindex="-1"></a>  <span class="fu">paste</span>(<span class="st">&quot;ballotposition_new ~ fct_gender_Male*n_women +&quot;</span>, .)</span>
<span id="cb24-56"><a href="#cb24-56" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-57"><a href="#cb24-57" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>respondent_gender_Male <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(df<span class="sc">$</span>respondent_gender <span class="sc">==</span> <span class="st">&quot;Male&quot;</span>)</span>
<span id="cb24-58"><a href="#cb24-58" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-59"><a href="#cb24-59" aria-hidden="true" tabindex="-1"></a>f2 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))] </span>
<span id="cb24-60"><a href="#cb24-60" aria-hidden="true" tabindex="-1"></a>f2 <span class="ot">&lt;-</span> f2[f2 <span class="sc">!=</span> <span class="st">&quot;fct_gender_Male&quot;</span>]</span>
<span id="cb24-61"><a href="#cb24-61" aria-hidden="true" tabindex="-1"></a>f2 <span class="ot">&lt;-</span> <span class="fu">paste</span>(f2, <span class="at">collapse =</span> <span class="st">&quot; + &quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb24-62"><a href="#cb24-62" aria-hidden="true" tabindex="-1"></a>  <span class="fu">paste</span>(<span class="st">&quot;ballotposition_new ~ fct_gender_Male*respondent_gender_Male +&quot;</span>, .)</span>
<span id="cb24-63"><a href="#cb24-63" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-64"><a href="#cb24-64" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>lr <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(df<span class="sc">$</span>qleftright1)</span>
<span id="cb24-65"><a href="#cb24-65" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-66"><a href="#cb24-66" aria-hidden="true" tabindex="-1"></a>f3 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))] </span>
<span id="cb24-67"><a href="#cb24-67" aria-hidden="true" tabindex="-1"></a>f3 <span class="ot">&lt;-</span> f3[f3 <span class="sc">!=</span> <span class="st">&quot;fct_gender_Male&quot;</span>]</span>
<span id="cb24-68"><a href="#cb24-68" aria-hidden="true" tabindex="-1"></a>f3 <span class="ot">&lt;-</span> <span class="fu">paste</span>(f3, <span class="at">collapse =</span> <span class="st">&quot; + &quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb24-69"><a href="#cb24-69" aria-hidden="true" tabindex="-1"></a>  <span class="fu">paste</span>(<span class="st">&quot;ballotposition_new ~ fct_gender_Male*lr +&quot;</span>, .)</span>
<span id="cb24-70"><a href="#cb24-70" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-71"><a href="#cb24-71" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>rightwing_party <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;FPÖ&quot;</span> <span class="sc">|</span> df<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;ÖVP&quot;</span>)</span>
<span id="cb24-72"><a href="#cb24-72" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-73"><a href="#cb24-73" aria-hidden="true" tabindex="-1"></a>f4 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))] </span>
<span id="cb24-74"><a href="#cb24-74" aria-hidden="true" tabindex="-1"></a>f4 <span class="ot">&lt;-</span> f4[f4 <span class="sc">!=</span> <span class="st">&quot;fct_gender_Male&quot;</span>]</span>
<span id="cb24-75"><a href="#cb24-75" aria-hidden="true" tabindex="-1"></a>f4 <span class="ot">&lt;-</span> <span class="fu">paste</span>(f4, <span class="at">collapse =</span> <span class="st">&quot; + &quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb24-76"><a href="#cb24-76" aria-hidden="true" tabindex="-1"></a>  <span class="fu">paste</span>(<span class="st">&quot;ballotposition_new ~ fct_gender_Male*rightwing_party +&quot;</span>, .)</span>
<span id="cb24-77"><a href="#cb24-77" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-78"><a href="#cb24-78" aria-hidden="true" tabindex="-1"></a><span class="co"># Baseline Model</span></span>
<span id="cb24-79"><a href="#cb24-79" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-80"><a href="#cb24-80" aria-hidden="true" tabindex="-1"></a>mod0 <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f0, </span>
<span id="cb24-81"><a href="#cb24-81" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> df,</span>
<span id="cb24-82"><a href="#cb24-82" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  133 (108 variable)
initial  value 5674.273995 
iter  10 value 5179.927439
iter  20 value 5108.088738
iter  30 value 5081.220137
iter  40 value 5077.175282
iter  50 value 5076.727721
iter  60 value 5076.677971
iter  70 value 5076.674636
final  value 5076.674472 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb26"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb26-1"><a href="#cb26-1" aria-hidden="true" tabindex="-1"></a>pred0 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod0,</span>
<span id="cb26-2"><a href="#cb26-2" aria-hidden="true" tabindex="-1"></a>                      <span class="at">data =</span> df,</span>
<span id="cb26-3"><a href="#cb26-3" aria-hidden="true" tabindex="-1"></a>                      <span class="at">x =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb26-4"><a href="#cb26-4" aria-hidden="true" tabindex="-1"></a>                      <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb26-5"><a href="#cb26-5" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb26-6"><a href="#cb26-6" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">1</span>),</span>
<span id="cb26-7"><a href="#cb26-7" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb26-8"><a href="#cb26-8" aria-hidden="true" tabindex="-1"></a>                      <span class="at">nsim =</span> <span class="dv">1000</span>, </span>
<span id="cb26-9"><a href="#cb26-9" aria-hidden="true" tabindex="-1"></a>                      <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb28"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb28-1"><a href="#cb28-1" aria-hidden="true" tabindex="-1"></a>pd0 <span class="ot">&lt;-</span> pred0<span class="sc">$</span>plotdata_fd <span class="sc">%&gt;%</span></span>
<span id="cb28-2"><a href="#cb28-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">0</span>)</span>
<span id="cb28-3"><a href="#cb28-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb28-4"><a href="#cb28-4" aria-hidden="true" tabindex="-1"></a>pd0<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd0<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb28-5"><a href="#cb28-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb28-6"><a href="#cb28-6" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd0<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb30"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb30-1"><a href="#cb30-1" aria-hidden="true" tabindex="-1"></a>pd0<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd0<span class="sc">$</span>ballotposition_new,</span>
<span id="cb30-2"><a href="#cb30-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb30-3"><a href="#cb30-3" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb30-4"><a href="#cb30-4" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb30-5"><a href="#cb30-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb30-6"><a href="#cb30-6" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE 1</span></span>
<span id="cb30-7"><a href="#cb30-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb30-8"><a href="#cb30-8" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd0, <span class="fu">aes</span>(<span class="at">x =</span> ballotposition_new, </span>
<span id="cb30-9"><a href="#cb30-9" aria-hidden="true" tabindex="-1"></a>                      <span class="at">y =</span> mean,</span>
<span id="cb30-10"><a href="#cb30-10" aria-hidden="true" tabindex="-1"></a>                      <span class="at">ymin =</span> lower, </span>
<span id="cb30-11"><a href="#cb30-11" aria-hidden="true" tabindex="-1"></a>                      <span class="at">ymax =</span> upper,</span>
<span id="cb30-12"><a href="#cb30-12" aria-hidden="true" tabindex="-1"></a>                      <span class="at">color =</span> ballotposition_new)) <span class="sc">+</span></span>
<span id="cb30-13"><a href="#cb30-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb30-14"><a href="#cb30-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span><span class="fl">0.05</span>,<span class="fl">0.10</span>,<span class="at">by=</span><span class="fl">0.05</span>), </span>
<span id="cb30-15"><a href="#cb30-15" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb30-16"><a href="#cb30-16" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb30-17"><a href="#cb30-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>() <span class="sc">+</span></span>
<span id="cb30-18"><a href="#cb30-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb30-19"><a href="#cb30-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;List Position&quot;</span>) <span class="sc">+</span></span>
<span id="cb30-20"><a href="#cb30-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb30-21"><a href="#cb30-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb30-22"><a href="#cb30-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span></span>
<span id="cb30-23"><a href="#cb30-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb30-24"><a href="#cb30-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb30-25"><a href="#cb30-25" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>())</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb31"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb31-1"><a href="#cb31-1" aria-hidden="true" tabindex="-1"></a><span class="co"># predicted values</span></span>
<span id="cb31-2"><a href="#cb31-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb31-3"><a href="#cb31-3" aria-hidden="true" tabindex="-1"></a>pd0pred <span class="ot">&lt;-</span> pred0<span class="sc">$</span>plotdata</span>
<span id="cb31-4"><a href="#cb31-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb31-5"><a href="#cb31-5" aria-hidden="true" tabindex="-1"></a><span class="fu">names</span>(pd0pred)[<span class="dv">1</span>] <span class="ot">&lt;-</span> <span class="st">&quot;xxx&quot;</span></span>
<span id="cb31-6"><a href="#cb31-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb31-7"><a href="#cb31-7" aria-hidden="true" tabindex="-1"></a>pd0pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd0pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb31-8"><a href="#cb31-8" aria-hidden="true" tabindex="-1"></a>                                     <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb31-9"><a href="#cb31-9" aria-hidden="true" tabindex="-1"></a>                                     <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd0pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb33"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb33-1"><a href="#cb33-1" aria-hidden="true" tabindex="-1"></a>pd0pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd0pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb33-2"><a href="#cb33-2" aria-hidden="true" tabindex="-1"></a>                                     <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb33-3"><a href="#cb33-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb33-4"><a href="#cb33-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb33-5"><a href="#cb33-5" aria-hidden="true" tabindex="-1"></a><span class="co"># APPENDIX H</span></span>
<span id="cb33-6"><a href="#cb33-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb33-7"><a href="#cb33-7" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd0pred, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>), </span>
<span id="cb33-8"><a href="#cb33-8" aria-hidden="true" tabindex="-1"></a>                           <span class="at">y =</span> mean,</span>
<span id="cb33-9"><a href="#cb33-9" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymin =</span> lower, </span>
<span id="cb33-10"><a href="#cb33-10" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymax =</span> upper,</span>
<span id="cb33-11"><a href="#cb33-11" aria-hidden="true" tabindex="-1"></a>                           <span class="at">color =</span> ballotposition_new)) <span class="sc">+</span></span>
<span id="cb33-12"><a href="#cb33-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">0.4</span>,<span class="at">by =</span> <span class="fl">0.1</span>), </span>
<span id="cb33-13"><a href="#cb33-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb33-14"><a href="#cb33-14" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb33-15"><a href="#cb33-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>(<span class="at">size =</span> .<span class="dv">3</span>, <span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> .<span class="dv">5</span>)) <span class="sc">+</span></span>
<span id="cb33-16"><a href="#cb33-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb33-17"><a href="#cb33-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>) <span class="sc">+</span></span>
<span id="cb33-18"><a href="#cb33-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb33-19"><a href="#cb33-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb33-20"><a href="#cb33-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;&quot;</span>, <span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span> </span>
<span id="cb33-21"><a href="#cb33-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb33-22"><a href="#cb33-22" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb33-23"><a href="#cb33-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.84</span>,.<span class="dv">13</span>),</span>
<span id="cb33-24"><a href="#cb33-24" aria-hidden="true" tabindex="-1"></a>        <span class="at">legend.box.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span></span>
<span id="cb33-25"><a href="#cb33-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>, <span class="at">shape =</span> <span class="st">&quot;none&quot;</span>, <span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb33-26"><a href="#cb33-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: A numeric `legend.position` argument in `theme()` was deprecated in ggplot2
3.5.0.
ℹ Please use the `legend.position.inside` argument of `theme()` instead.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb35"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb35-1"><a href="#cb35-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Model times gender of respondents</span></span>
<span id="cb35-2"><a href="#cb35-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb35-3"><a href="#cb35-3" aria-hidden="true" tabindex="-1"></a>mod2 <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f2, </span>
<span id="cb35-4"><a href="#cb35-4" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> df,</span>
<span id="cb35-5"><a href="#cb35-5" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 5674.273995 
iter  10 value 5158.767802
iter  20 value 5097.457173
iter  30 value 5073.639106
iter  40 value 5068.699640
iter  50 value 5067.970000
iter  60 value 5067.896430
iter  70 value 5067.891363
final  value 5067.890657 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb37"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb37-1"><a href="#cb37-1" aria-hidden="true" tabindex="-1"></a>pred2 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod2,</span>
<span id="cb37-2"><a href="#cb37-2" aria-hidden="true" tabindex="-1"></a>                    <span class="at">data =</span> df,</span>
<span id="cb37-3"><a href="#cb37-3" aria-hidden="true" tabindex="-1"></a>                    <span class="at">x =</span> <span class="st">&quot;respondent_gender_Male&quot;</span>,</span>
<span id="cb37-4"><a href="#cb37-4" aria-hidden="true" tabindex="-1"></a>                    <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb37-5"><a href="#cb37-5" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb37-6"><a href="#cb37-6" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb37-7"><a href="#cb37-7" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb37-8"><a href="#cb37-8" aria-hidden="true" tabindex="-1"></a>                    <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb37-9"><a href="#cb37-9" aria-hidden="true" tabindex="-1"></a>                    <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb39"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb39-1"><a href="#cb39-1" aria-hidden="true" tabindex="-1"></a>pd2 <span class="ot">&lt;-</span> pred2<span class="sc">$</span>plotdata_fd </span>
<span id="cb39-2"><a href="#cb39-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb39-3"><a href="#cb39-3" aria-hidden="true" tabindex="-1"></a>pd2<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd2<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb39-4"><a href="#cb39-4" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb39-5"><a href="#cb39-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd2<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd2$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb41"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb41-1"><a href="#cb41-1" aria-hidden="true" tabindex="-1"></a>pd2<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd2<span class="sc">$</span>ballotposition_new,</span>
<span id="cb41-2"><a href="#cb41-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb41-3"><a href="#cb41-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb41-4"><a href="#cb41-4" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE 3</span></span>
<span id="cb41-5"><a href="#cb41-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb41-6"><a href="#cb41-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd2, <span class="fu">aes</span>(<span class="at">x =</span> ballotposition_new, </span>
<span id="cb41-7"><a href="#cb41-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb41-8"><a href="#cb41-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb41-9"><a href="#cb41-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper)) <span class="sc">+</span></span>
<span id="cb41-10"><a href="#cb41-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_vline</span>(<span class="fu">aes</span>(<span class="at">xintercept =</span> ballotposition_new), </span>
<span id="cb41-11"><a href="#cb41-11" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb41-12"><a href="#cb41-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb41-13"><a href="#cb41-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb41-14"><a href="#cb41-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>(<span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> <span class="fl">0.5</span>),</span>
<span id="cb41-15"><a href="#cb41-15" aria-hidden="true" tabindex="-1"></a>                  <span class="fu">aes</span>(<span class="at">color =</span> <span class="fu">ifelse</span>(respondent_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb41-16"><a href="#cb41-16" aria-hidden="true" tabindex="-1"></a>                      <span class="at">shape =</span> <span class="fu">ifelse</span>(respondent_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb41-17"><a href="#cb41-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb41-18"><a href="#cb41-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;List Position&quot;</span>) <span class="sc">+</span></span>
<span id="cb41-19"><a href="#cb41-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb41-20"><a href="#cb41-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb41-21"><a href="#cb41-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Respondent&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb41-22"><a href="#cb41-22" aria-hidden="true" tabindex="-1"></a>                                                     <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb41-23"><a href="#cb41-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_shape_manual</span>(<span class="st">&quot;Respondent&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="dv">15</span>,<span class="dv">16</span>)) <span class="sc">+</span> </span>
<span id="cb41-24"><a href="#cb41-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb41-25"><a href="#cb41-25" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb41-26"><a href="#cb41-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb42"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb42-1"><a href="#cb42-1" aria-hidden="true" tabindex="-1"></a>pd2pred <span class="ot">&lt;-</span> pred2<span class="sc">$</span>plotdata</span>
<span id="cb42-2"><a href="#cb42-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb42-3"><a href="#cb42-3" aria-hidden="true" tabindex="-1"></a>pd2pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd2pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb42-4"><a href="#cb42-4" aria-hidden="true" tabindex="-1"></a>                                     <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb42-5"><a href="#cb42-5" aria-hidden="true" tabindex="-1"></a>                                     <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd2pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd2pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb44"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb44-1"><a href="#cb44-1" aria-hidden="true" tabindex="-1"></a>pd2pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd2pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb44-2"><a href="#cb44-2" aria-hidden="true" tabindex="-1"></a>                                     <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb44-3"><a href="#cb44-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb44-4"><a href="#cb44-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb44-5"><a href="#cb44-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd2pred, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">ifelse</span>(respondent_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>), </span>
<span id="cb44-6"><a href="#cb44-6" aria-hidden="true" tabindex="-1"></a>                           <span class="at">y =</span> mean,</span>
<span id="cb44-7"><a href="#cb44-7" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymin =</span> lower, </span>
<span id="cb44-8"><a href="#cb44-8" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymax =</span> upper,</span>
<span id="cb44-9"><a href="#cb44-9" aria-hidden="true" tabindex="-1"></a>                           <span class="at">shape =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb44-10"><a href="#cb44-10" aria-hidden="true" tabindex="-1"></a>                           <span class="at">color =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb44-11"><a href="#cb44-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">0.4</span>,<span class="at">by =</span> <span class="fl">0.1</span>), </span>
<span id="cb44-12"><a href="#cb44-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb44-13"><a href="#cb44-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb44-14"><a href="#cb44-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>(<span class="at">size =</span> .<span class="dv">3</span>, <span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> .<span class="dv">5</span>)) <span class="sc">+</span></span>
<span id="cb44-15"><a href="#cb44-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb44-16"><a href="#cb44-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Respondent&#39;s Gender&quot;</span>) <span class="sc">+</span></span>
<span id="cb44-17"><a href="#cb44-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb44-18"><a href="#cb44-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb44-19"><a href="#cb44-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_shape_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="dv">15</span><span class="sc">:</span><span class="dv">16</span>)) <span class="sc">+</span> </span>
<span id="cb44-20"><a href="#cb44-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb44-21"><a href="#cb44-21" aria-hidden="true" tabindex="-1"></a>                                                     <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb44-22"><a href="#cb44-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb44-23"><a href="#cb44-23" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb44-24"><a href="#cb44-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.84</span>,.<span class="dv">13</span>)) <span class="sc">+</span></span>
<span id="cb44-25"><a href="#cb44-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
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<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb45"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb45-1"><a href="#cb45-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Model times supply</span></span>
<span id="cb45-2"><a href="#cb45-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb45-3"><a href="#cb45-3" aria-hidden="true" tabindex="-1"></a>mod1 <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f1, </span>
<span id="cb45-4"><a href="#cb45-4" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> df,</span>
<span id="cb45-5"><a href="#cb45-5" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 5674.273995 
iter  10 value 5172.158531
iter  20 value 5115.846553
iter  30 value 5065.447053
iter  40 value 5054.254485
iter  50 value 5053.209689
iter  60 value 5053.099421
iter  70 value 5053.088487
final  value 5053.087304 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb47"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb47-1"><a href="#cb47-1" aria-hidden="true" tabindex="-1"></a>pred1 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod1,</span>
<span id="cb47-2"><a href="#cb47-2" aria-hidden="true" tabindex="-1"></a>                        <span class="at">data =</span> df,</span>
<span id="cb47-3"><a href="#cb47-3" aria-hidden="true" tabindex="-1"></a>                        <span class="at">x =</span> <span class="st">&quot;n_women&quot;</span>,</span>
<span id="cb47-4"><a href="#cb47-4" aria-hidden="true" tabindex="-1"></a>                        <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb47-5"><a href="#cb47-5" aria-hidden="true" tabindex="-1"></a>                        <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb47-6"><a href="#cb47-6" aria-hidden="true" tabindex="-1"></a>                        <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb47-7"><a href="#cb47-7" aria-hidden="true" tabindex="-1"></a>                        <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb47-8"><a href="#cb47-8" aria-hidden="true" tabindex="-1"></a>                        <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb47-9"><a href="#cb47-9" aria-hidden="true" tabindex="-1"></a>                        <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb49"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb49-1"><a href="#cb49-1" aria-hidden="true" tabindex="-1"></a>pd1 <span class="ot">&lt;-</span> pred1<span class="sc">$</span>plotdata_fd</span>
<span id="cb49-2"><a href="#cb49-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb49-3"><a href="#cb49-3" aria-hidden="true" tabindex="-1"></a>pd1<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd1<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb49-4"><a href="#cb49-4" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb49-5"><a href="#cb49-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd1<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd1$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb51"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb51-1"><a href="#cb51-1" aria-hidden="true" tabindex="-1"></a>pd1<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd1<span class="sc">$</span>ballotposition_new,</span>
<span id="cb51-2"><a href="#cb51-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb51-3"><a href="#cb51-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb51-4"><a href="#cb51-4" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE 2</span></span>
<span id="cb51-5"><a href="#cb51-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb51-6"><a href="#cb51-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd1, <span class="fu">aes</span>(<span class="at">x =</span> n_women, </span>
<span id="cb51-7"><a href="#cb51-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb51-8"><a href="#cb51-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb51-9"><a href="#cb51-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb51-10"><a href="#cb51-10" aria-hidden="true" tabindex="-1"></a>                       <span class="at">fill =</span> ballotposition_new)) <span class="sc">+</span></span>
<span id="cb51-11"><a href="#cb51-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span>.<span class="dv">2</span>,.<span class="dv">2</span>,<span class="at">by=</span>.<span class="dv">1</span>), </span>
<span id="cb51-12"><a href="#cb51-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb51-13"><a href="#cb51-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb51-14"><a href="#cb51-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb51-15"><a href="#cb51-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>) <span class="sc">+</span></span>
<span id="cb51-16"><a href="#cb51-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb51-17"><a href="#cb51-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb51-18"><a href="#cb51-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;# Female Aspirants at Stage 1&quot;</span>) <span class="sc">+</span></span>
<span id="cb51-19"><a href="#cb51-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">8</span>) <span class="sc">+</span></span>
<span id="cb51-20"><a href="#cb51-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb51-21"><a href="#cb51-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb51-22"><a href="#cb51-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;# Female Aspirtants&quot;</span>, <span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span> </span>
<span id="cb51-23"><a href="#cb51-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb51-24"><a href="#cb51-24" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb51-25"><a href="#cb51-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>) <span class="sc">+</span></span>
<span id="cb51-26"><a href="#cb51-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="data:image/png;base64,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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb52"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb52-1"><a href="#cb52-1" aria-hidden="true" tabindex="-1"></a>pd1pred <span class="ot">&lt;-</span> pred1<span class="sc">$</span>plotdata</span>
<span id="cb52-2"><a href="#cb52-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb52-3"><a href="#cb52-3" aria-hidden="true" tabindex="-1"></a>pd1pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd1pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb52-4"><a href="#cb52-4" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb52-5"><a href="#cb52-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd1pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd1pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb54"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb54-1"><a href="#cb54-1" aria-hidden="true" tabindex="-1"></a>pd1pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd1pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb54-2"><a href="#cb54-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb54-3"><a href="#cb54-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb54-4"><a href="#cb54-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb54-5"><a href="#cb54-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd1pred, <span class="fu">aes</span>(<span class="at">x =</span> n_women, </span>
<span id="cb54-6"><a href="#cb54-6" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb54-7"><a href="#cb54-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb54-8"><a href="#cb54-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb54-9"><a href="#cb54-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">fill =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb54-10"><a href="#cb54-10" aria-hidden="true" tabindex="-1"></a>                       <span class="at">color =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb54-11"><a href="#cb54-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">0.4</span>,<span class="at">by =</span> <span class="fl">0.1</span>), </span>
<span id="cb54-12"><a href="#cb54-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb54-13"><a href="#cb54-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb54-14"><a href="#cb54-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>, <span class="at">color =</span> <span class="cn">NA</span>) <span class="sc">+</span></span>
<span id="cb54-15"><a href="#cb54-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb54-16"><a href="#cb54-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb54-17"><a href="#cb54-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;# Female Aspirants at Stage 1&quot;</span>) <span class="sc">+</span></span>
<span id="cb54-18"><a href="#cb54-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">8</span>) <span class="sc">+</span></span>
<span id="cb54-19"><a href="#cb54-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb54-20"><a href="#cb54-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb54-21"><a href="#cb54-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb54-22"><a href="#cb54-22" aria-hidden="true" tabindex="-1"></a>                                                      <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb54-23"><a href="#cb54-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb54-24"><a href="#cb54-24" aria-hidden="true" tabindex="-1"></a>                                                      <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb54-25"><a href="#cb54-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb54-26"><a href="#cb54-26" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb54-27"><a href="#cb54-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.84</span>,.<span class="dv">13</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb55"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb55-1"><a href="#cb55-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Model times leftright</span></span>
<span id="cb55-2"><a href="#cb55-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb55-3"><a href="#cb55-3" aria-hidden="true" tabindex="-1"></a>mod3 <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f3, </span>
<span id="cb55-4"><a href="#cb55-4" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> df,</span>
<span id="cb55-5"><a href="#cb55-5" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 5674.273995 
iter  10 value 5222.776399
iter  20 value 5140.212492
iter  30 value 5079.833371
iter  40 value 5070.029027
iter  50 value 5068.043944
iter  60 value 5067.832433
iter  70 value 5067.811742
iter  80 value 5067.809931
final  value 5067.809802 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb57"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb57-1"><a href="#cb57-1" aria-hidden="true" tabindex="-1"></a>pred3 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod3,</span>
<span id="cb57-2"><a href="#cb57-2" aria-hidden="true" tabindex="-1"></a>                    <span class="at">data =</span> df,</span>
<span id="cb57-3"><a href="#cb57-3" aria-hidden="true" tabindex="-1"></a>                    <span class="at">x =</span> <span class="st">&quot;lr&quot;</span>,</span>
<span id="cb57-4"><a href="#cb57-4" aria-hidden="true" tabindex="-1"></a>                    <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb57-5"><a href="#cb57-5" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb57-6"><a href="#cb57-6" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb57-7"><a href="#cb57-7" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb57-8"><a href="#cb57-8" aria-hidden="true" tabindex="-1"></a>                    <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb57-9"><a href="#cb57-9" aria-hidden="true" tabindex="-1"></a>                    <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb59"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb59-1"><a href="#cb59-1" aria-hidden="true" tabindex="-1"></a>pd3 <span class="ot">&lt;-</span> pred3<span class="sc">$</span>plotdata_fd</span>
<span id="cb59-2"><a href="#cb59-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb59-3"><a href="#cb59-3" aria-hidden="true" tabindex="-1"></a>pd3<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd3<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb59-4"><a href="#cb59-4" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb59-5"><a href="#cb59-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd3<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd3$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb61"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb61-1"><a href="#cb61-1" aria-hidden="true" tabindex="-1"></a>pd3<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd3<span class="sc">$</span>ballotposition_new,</span>
<span id="cb61-2"><a href="#cb61-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb61-3"><a href="#cb61-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb61-4"><a href="#cb61-4" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE A22 (SECTION I)</span></span>
<span id="cb61-5"><a href="#cb61-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb61-6"><a href="#cb61-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd3, <span class="fu">aes</span>(<span class="at">x =</span> lr, </span>
<span id="cb61-7"><a href="#cb61-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb61-8"><a href="#cb61-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb61-9"><a href="#cb61-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb61-10"><a href="#cb61-10" aria-hidden="true" tabindex="-1"></a>                       <span class="at">fill =</span> ballotposition_new)) <span class="sc">+</span></span>
<span id="cb61-11"><a href="#cb61-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span>.<span class="dv">2</span>,.<span class="dv">2</span>,<span class="at">by=</span>.<span class="dv">1</span>), </span>
<span id="cb61-12"><a href="#cb61-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb61-13"><a href="#cb61-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb61-14"><a href="#cb61-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb61-15"><a href="#cb61-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>) <span class="sc">+</span></span>
<span id="cb61-16"><a href="#cb61-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb61-17"><a href="#cb61-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb61-18"><a href="#cb61-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Left-Right&quot;</span>) <span class="sc">+</span></span>
<span id="cb61-19"><a href="#cb61-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>) <span class="sc">+</span></span>
<span id="cb61-20"><a href="#cb61-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb61-21"><a href="#cb61-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb61-22"><a href="#cb61-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;# Female Aspirtants&quot;</span>, <span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span> </span>
<span id="cb61-23"><a href="#cb61-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb61-24"><a href="#cb61-24" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb61-25"><a href="#cb61-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>) <span class="sc">+</span></span>
<span id="cb61-26"><a href="#cb61-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="data:image/png;base64,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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb62"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb62-1"><a href="#cb62-1" aria-hidden="true" tabindex="-1"></a>pd3pred <span class="ot">&lt;-</span> pred3<span class="sc">$</span>plotdata</span>
<span id="cb62-2"><a href="#cb62-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb62-3"><a href="#cb62-3" aria-hidden="true" tabindex="-1"></a>pd3pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd3pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb62-4"><a href="#cb62-4" aria-hidden="true" tabindex="-1"></a>                                     <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb62-5"><a href="#cb62-5" aria-hidden="true" tabindex="-1"></a>                                     <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd3pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd3pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb64"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb64-1"><a href="#cb64-1" aria-hidden="true" tabindex="-1"></a>pd3pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd3pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb64-2"><a href="#cb64-2" aria-hidden="true" tabindex="-1"></a>                                     <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb64-3"><a href="#cb64-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb64-4"><a href="#cb64-4" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd3pred, <span class="fu">aes</span>(<span class="at">x =</span> lr, </span>
<span id="cb64-5"><a href="#cb64-5" aria-hidden="true" tabindex="-1"></a>                           <span class="at">y =</span> mean,</span>
<span id="cb64-6"><a href="#cb64-6" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymin =</span> lower, </span>
<span id="cb64-7"><a href="#cb64-7" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymax =</span> upper,</span>
<span id="cb64-8"><a href="#cb64-8" aria-hidden="true" tabindex="-1"></a>                           <span class="at">fill =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb64-9"><a href="#cb64-9" aria-hidden="true" tabindex="-1"></a>                           <span class="at">color =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb64-10"><a href="#cb64-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">0.4</span>,<span class="at">by =</span> <span class="fl">0.1</span>), </span>
<span id="cb64-11"><a href="#cb64-11" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb64-12"><a href="#cb64-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb64-13"><a href="#cb64-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>, <span class="at">color =</span> <span class="cn">NA</span>) <span class="sc">+</span></span>
<span id="cb64-14"><a href="#cb64-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb64-15"><a href="#cb64-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb64-16"><a href="#cb64-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Left-Right&quot;</span>) <span class="sc">+</span></span>
<span id="cb64-17"><a href="#cb64-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>) <span class="sc">+</span></span>
<span id="cb64-18"><a href="#cb64-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb64-19"><a href="#cb64-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb64-20"><a href="#cb64-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb64-21"><a href="#cb64-21" aria-hidden="true" tabindex="-1"></a>                                                    <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb64-22"><a href="#cb64-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb64-23"><a href="#cb64-23" aria-hidden="true" tabindex="-1"></a>                                                     <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb64-24"><a href="#cb64-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb64-25"><a href="#cb64-25" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb64-26"><a href="#cb64-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.84</span>,.<span class="dv">13</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb65"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb65-1"><a href="#cb65-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Model times lr party</span></span>
<span id="cb65-2"><a href="#cb65-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb65-3"><a href="#cb65-3" aria-hidden="true" tabindex="-1"></a>mod4 <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f4, </span>
<span id="cb65-4"><a href="#cb65-4" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> df,</span>
<span id="cb65-5"><a href="#cb65-5" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 5674.273995 
iter  10 value 5174.074014
iter  20 value 5105.375615
iter  30 value 5077.593206
iter  40 value 5070.816845
iter  50 value 5070.229354
iter  60 value 5070.156924
iter  70 value 5070.152655
final  value 5070.152493 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb67"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb67-1"><a href="#cb67-1" aria-hidden="true" tabindex="-1"></a>pred4 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod4,</span>
<span id="cb67-2"><a href="#cb67-2" aria-hidden="true" tabindex="-1"></a>                    <span class="at">data =</span> df,</span>
<span id="cb67-3"><a href="#cb67-3" aria-hidden="true" tabindex="-1"></a>                    <span class="at">x =</span> <span class="st">&quot;rightwing_party&quot;</span>,</span>
<span id="cb67-4"><a href="#cb67-4" aria-hidden="true" tabindex="-1"></a>                    <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb67-5"><a href="#cb67-5" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb67-6"><a href="#cb67-6" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb67-7"><a href="#cb67-7" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb67-8"><a href="#cb67-8" aria-hidden="true" tabindex="-1"></a>                    <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb67-9"><a href="#cb67-9" aria-hidden="true" tabindex="-1"></a>                    <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb69"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb69-1"><a href="#cb69-1" aria-hidden="true" tabindex="-1"></a>pd4 <span class="ot">&lt;-</span> pred4<span class="sc">$</span>plotdata_fd </span>
<span id="cb69-2"><a href="#cb69-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb69-3"><a href="#cb69-3" aria-hidden="true" tabindex="-1"></a>pd4<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd4<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb69-4"><a href="#cb69-4" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb69-5"><a href="#cb69-5" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd4<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd4$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb71"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb71-1"><a href="#cb71-1" aria-hidden="true" tabindex="-1"></a>pd4<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd4<span class="sc">$</span>ballotposition_new,</span>
<span id="cb71-2"><a href="#cb71-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb71-3"><a href="#cb71-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb71-4"><a href="#cb71-4" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd4, <span class="fu">aes</span>(<span class="at">x =</span> ballotposition_new, </span>
<span id="cb71-5"><a href="#cb71-5" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb71-6"><a href="#cb71-6" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb71-7"><a href="#cb71-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper)) <span class="sc">+</span></span>
<span id="cb71-8"><a href="#cb71-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_vline</span>(<span class="fu">aes</span>(<span class="at">xintercept =</span> ballotposition_new), </span>
<span id="cb71-9"><a href="#cb71-9" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb71-10"><a href="#cb71-10" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb71-11"><a href="#cb71-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb71-12"><a href="#cb71-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>(<span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> <span class="fl">0.5</span>),</span>
<span id="cb71-13"><a href="#cb71-13" aria-hidden="true" tabindex="-1"></a>                  <span class="fu">aes</span>(<span class="at">color =</span> <span class="fu">ifelse</span>(rightwing_party <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;ÖVP/FPÖ&quot;</span>, <span class="st">&quot;NEOS/Greens/SPÖ&quot;</span>),</span>
<span id="cb71-14"><a href="#cb71-14" aria-hidden="true" tabindex="-1"></a>                      <span class="at">shape =</span> <span class="fu">ifelse</span>(rightwing_party <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;ÖVP/FPÖ&quot;</span>, <span class="st">&quot;NEOS/Greens/SPÖ&quot;</span>))) <span class="sc">+</span></span>
<span id="cb71-15"><a href="#cb71-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb71-16"><a href="#cb71-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;List Position&quot;</span>) <span class="sc">+</span></span>
<span id="cb71-17"><a href="#cb71-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb71-18"><a href="#cb71-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb71-19"><a href="#cb71-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Respondent&#39;s Party&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb71-20"><a href="#cb71-20" aria-hidden="true" tabindex="-1"></a>                                                       <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb71-21"><a href="#cb71-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_shape_manual</span>(<span class="st">&quot;Respondent&#39;s Party&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="dv">15</span>,<span class="dv">16</span>)) <span class="sc">+</span> </span>
<span id="cb71-22"><a href="#cb71-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb71-23"><a href="#cb71-23" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb71-24"><a href="#cb71-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb72"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb72-1"><a href="#cb72-1" aria-hidden="true" tabindex="-1"></a>pd4pred <span class="ot">&lt;-</span> pred4<span class="sc">$</span>plotdata</span>
<span id="cb72-2"><a href="#cb72-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb72-3"><a href="#cb72-3" aria-hidden="true" tabindex="-1"></a>pd4pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd4pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb72-4"><a href="#cb72-4" aria-hidden="true" tabindex="-1"></a>                                     <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb72-5"><a href="#cb72-5" aria-hidden="true" tabindex="-1"></a>                                     <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd4pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd4pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb74"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb74-1"><a href="#cb74-1" aria-hidden="true" tabindex="-1"></a>pd4pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd4pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb74-2"><a href="#cb74-2" aria-hidden="true" tabindex="-1"></a>                                     <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb74-3"><a href="#cb74-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb74-4"><a href="#cb74-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb74-5"><a href="#cb74-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd4pred, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">ifelse</span>(rightwing_party <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;ÖVP/FPÖ&quot;</span>, <span class="st">&quot;NEOS/Greens/SPÖ&quot;</span>), </span>
<span id="cb74-6"><a href="#cb74-6" aria-hidden="true" tabindex="-1"></a>                           <span class="at">y =</span> mean,</span>
<span id="cb74-7"><a href="#cb74-7" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymin =</span> lower, </span>
<span id="cb74-8"><a href="#cb74-8" aria-hidden="true" tabindex="-1"></a>                           <span class="at">ymax =</span> upper,</span>
<span id="cb74-9"><a href="#cb74-9" aria-hidden="true" tabindex="-1"></a>                           <span class="at">shape =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb74-10"><a href="#cb74-10" aria-hidden="true" tabindex="-1"></a>                           <span class="at">color =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb74-11"><a href="#cb74-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">0.4</span>,<span class="at">by =</span> <span class="fl">0.1</span>), </span>
<span id="cb74-12"><a href="#cb74-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb74-13"><a href="#cb74-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb74-14"><a href="#cb74-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb74-15"><a href="#cb74-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>(<span class="at">size =</span> .<span class="dv">3</span>, <span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> .<span class="dv">5</span>)) <span class="sc">+</span></span>
<span id="cb74-16"><a href="#cb74-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb74-17"><a href="#cb74-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Respondent&#39;s Party&quot;</span>) <span class="sc">+</span></span>
<span id="cb74-18"><a href="#cb74-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb74-19"><a href="#cb74-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb74-20"><a href="#cb74-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_shape_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="dv">15</span><span class="sc">:</span><span class="dv">16</span>)) <span class="sc">+</span> </span>
<span id="cb74-21"><a href="#cb74-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb74-22"><a href="#cb74-22" aria-hidden="true" tabindex="-1"></a>                                                     <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb74-23"><a href="#cb74-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb74-24"><a href="#cb74-24" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb74-25"><a href="#cb74-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.84</span>,.<span class="dv">13</span>),</span>
<span id="cb74-26"><a href="#cb74-26" aria-hidden="true" tabindex="-1"></a>        <span class="at">legend.box.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&quot;steelblue&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb75"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb75-1"><a href="#cb75-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Leftright * Gender</span></span>
<span id="cb75-2"><a href="#cb75-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb75-3"><a href="#cb75-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Model times leftright</span></span>
<span id="cb75-4"><a href="#cb75-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb75-5"><a href="#cb75-5" aria-hidden="true" tabindex="-1"></a>dfm <span class="ot">&lt;-</span> <span class="fu">filter</span>(df, respondent_gender <span class="sc">==</span> <span class="st">&quot;Male&quot;</span>)</span>
<span id="cb75-6"><a href="#cb75-6" aria-hidden="true" tabindex="-1"></a>dff <span class="ot">&lt;-</span> <span class="fu">filter</span>(df, respondent_gender <span class="sc">==</span> <span class="st">&quot;Female&quot;</span>)</span>
<span id="cb75-7"><a href="#cb75-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb75-8"><a href="#cb75-8" aria-hidden="true" tabindex="-1"></a>mod3m <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f3, </span>
<span id="cb75-9"><a href="#cb75-9" aria-hidden="true" tabindex="-1"></a>                 <span class="at">data =</span> dfm,</span>
<span id="cb75-10"><a href="#cb75-10" aria-hidden="true" tabindex="-1"></a>                 <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 3940.468052 
iter  10 value 3597.489071
iter  20 value 3554.590428
iter  30 value 3530.729997
iter  40 value 3526.381984
iter  50 value 3525.991155
iter  60 value 3525.903218
iter  70 value 3525.899772
iter  70 value 3525.899739
iter  70 value 3525.899738
final  value 3525.899738 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb77"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb77-1"><a href="#cb77-1" aria-hidden="true" tabindex="-1"></a>mod3f <span class="ot">&lt;-</span> <span class="fu">multinom</span>(f3, </span>
<span id="cb77-2"><a href="#cb77-2" aria-hidden="true" tabindex="-1"></a>                  <span class="at">data =</span> dff,</span>
<span id="cb77-3"><a href="#cb77-3" aria-hidden="true" tabindex="-1"></a>                  <span class="at">Hess =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># weights:  147 (120 variable)
initial  value 1733.805943 
iter  10 value 1601.561951
iter  20 value 1497.006538
iter  30 value 1480.048437
iter  40 value 1479.330255
iter  50 value 1479.224924
iter  60 value 1479.201767
iter  70 value 1479.199869
final  value 1479.199753 
converged</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb79"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb79-1"><a href="#cb79-1" aria-hidden="true" tabindex="-1"></a>pred3m <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod3m,</span>
<span id="cb79-2"><a href="#cb79-2" aria-hidden="true" tabindex="-1"></a>                    <span class="at">data =</span> dfm,</span>
<span id="cb79-3"><a href="#cb79-3" aria-hidden="true" tabindex="-1"></a>                    <span class="at">x =</span> <span class="st">&quot;lr&quot;</span>,</span>
<span id="cb79-4"><a href="#cb79-4" aria-hidden="true" tabindex="-1"></a>                    <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb79-5"><a href="#cb79-5" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb79-6"><a href="#cb79-6" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb79-7"><a href="#cb79-7" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb79-8"><a href="#cb79-8" aria-hidden="true" tabindex="-1"></a>                    <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb79-9"><a href="#cb79-9" aria-hidden="true" tabindex="-1"></a>                    <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb81"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb81-1"><a href="#cb81-1" aria-hidden="true" tabindex="-1"></a>pred3f <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod3f,</span>
<span id="cb81-2"><a href="#cb81-2" aria-hidden="true" tabindex="-1"></a>                     <span class="at">data =</span> dff,</span>
<span id="cb81-3"><a href="#cb81-3" aria-hidden="true" tabindex="-1"></a>                     <span class="at">x =</span> <span class="st">&quot;lr&quot;</span>,</span>
<span id="cb81-4"><a href="#cb81-4" aria-hidden="true" tabindex="-1"></a>                     <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb81-5"><a href="#cb81-5" aria-hidden="true" tabindex="-1"></a>                     <span class="at">z =</span> <span class="st">&quot;fct_gender_Male&quot;</span>,</span>
<span id="cb81-6"><a href="#cb81-6" aria-hidden="true" tabindex="-1"></a>                     <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">1</span>),</span>
<span id="cb81-7"><a href="#cb81-7" aria-hidden="true" tabindex="-1"></a>                     <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb81-8"><a href="#cb81-8" aria-hidden="true" tabindex="-1"></a>                     <span class="at">nsim =</span> <span class="dv">1000</span>, <span class="co"># faster</span></span>
<span id="cb81-9"><a href="#cb81-9" aria-hidden="true" tabindex="-1"></a>                     <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb83"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb83-1"><a href="#cb83-1" aria-hidden="true" tabindex="-1"></a>pd3m <span class="ot">&lt;-</span> pred3m<span class="sc">$</span>plotdata_fd</span>
<span id="cb83-2"><a href="#cb83-2" aria-hidden="true" tabindex="-1"></a>pd3m<span class="sc">$</span>respondent_gender <span class="ot">&lt;-</span> <span class="st">&quot;Male&quot;</span></span>
<span id="cb83-3"><a href="#cb83-3" aria-hidden="true" tabindex="-1"></a>pd3f <span class="ot">&lt;-</span> pred3f<span class="sc">$</span>plotdata_fd</span>
<span id="cb83-4"><a href="#cb83-4" aria-hidden="true" tabindex="-1"></a>pd3f<span class="sc">$</span>respondent_gender <span class="ot">&lt;-</span> <span class="st">&quot;Female&quot;</span></span>
<span id="cb83-5"><a href="#cb83-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb83-6"><a href="#cb83-6" aria-hidden="true" tabindex="-1"></a>pd3m_pred <span class="ot">&lt;-</span> pred3m<span class="sc">$</span>plotdata</span>
<span id="cb83-7"><a href="#cb83-7" aria-hidden="true" tabindex="-1"></a>pd3m_pred<span class="sc">$</span>respondent_gender <span class="ot">&lt;-</span> <span class="st">&quot;Male&quot;</span></span>
<span id="cb83-8"><a href="#cb83-8" aria-hidden="true" tabindex="-1"></a>pd3f_pred <span class="ot">&lt;-</span> pred3f<span class="sc">$</span>plotdata</span>
<span id="cb83-9"><a href="#cb83-9" aria-hidden="true" tabindex="-1"></a>pd3f_pred<span class="sc">$</span>respondent_gender <span class="ot">&lt;-</span> <span class="st">&quot;Female&quot;</span></span>
<span id="cb83-10"><a href="#cb83-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb83-11"><a href="#cb83-11" aria-hidden="true" tabindex="-1"></a>pd3 <span class="ot">&lt;-</span> <span class="fu">bind_rows</span>(pd3m,pd3f)</span>
<span id="cb83-12"><a href="#cb83-12" aria-hidden="true" tabindex="-1"></a>pd3_pred <span class="ot">&lt;-</span> <span class="fu">bind_rows</span>(pd3m_pred,pd3f_pred)</span>
<span id="cb83-13"><a href="#cb83-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb83-14"><a href="#cb83-14" aria-hidden="true" tabindex="-1"></a>pd3<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd3<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb83-15"><a href="#cb83-15" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb83-16"><a href="#cb83-16" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd3<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd3$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb85"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb85-1"><a href="#cb85-1" aria-hidden="true" tabindex="-1"></a>pd3<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd3<span class="sc">$</span>ballotposition_new,</span>
<span id="cb85-2"><a href="#cb85-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb85-3"><a href="#cb85-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb85-4"><a href="#cb85-4" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE A23</span></span>
<span id="cb85-5"><a href="#cb85-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb85-6"><a href="#cb85-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd3, <span class="fu">aes</span>(<span class="at">x =</span> lr, </span>
<span id="cb85-7"><a href="#cb85-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb85-8"><a href="#cb85-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb85-9"><a href="#cb85-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb85-10"><a href="#cb85-10" aria-hidden="true" tabindex="-1"></a>                       <span class="at">fill =</span> respondent_gender,</span>
<span id="cb85-11"><a href="#cb85-11" aria-hidden="true" tabindex="-1"></a>                       <span class="at">color =</span> respondent_gender)) <span class="sc">+</span></span>
<span id="cb85-12"><a href="#cb85-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span>.<span class="dv">2</span>,.<span class="dv">2</span>,<span class="at">by=</span>.<span class="dv">1</span>), </span>
<span id="cb85-13"><a href="#cb85-13" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb85-14"><a href="#cb85-14" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb85-15"><a href="#cb85-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb85-16"><a href="#cb85-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>, <span class="at">color =</span> <span class="cn">NA</span>) <span class="sc">+</span></span>
<span id="cb85-17"><a href="#cb85-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb85-18"><a href="#cb85-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb85-19"><a href="#cb85-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Left-Right&quot;</span>) <span class="sc">+</span></span>
<span id="cb85-20"><a href="#cb85-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>) <span class="sc">+</span></span>
<span id="cb85-21"><a href="#cb85-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect of Male vs. Female Aspirant&quot;</span>) <span class="sc">+</span></span>
<span id="cb85-22"><a href="#cb85-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb85-23"><a href="#cb85-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;Respondent&#39;s Gender&quot;</span>, </span>
<span id="cb85-24"><a href="#cb85-24" aria-hidden="true" tabindex="-1"></a>                    <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb85-25"><a href="#cb85-25" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb85-26"><a href="#cb85-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Respondent&#39;s Gender&quot;</span>, </span>
<span id="cb85-27"><a href="#cb85-27" aria-hidden="true" tabindex="-1"></a>                    <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb85-28"><a href="#cb85-28" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb85-29"><a href="#cb85-29" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb85-30"><a href="#cb85-30" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb85-31"><a href="#cb85-31" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="fu">c</span>(<span class="fl">0.8</span>, <span class="fl">0.15</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb86"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb86-1"><a href="#cb86-1" aria-hidden="true" tabindex="-1"></a>pd3_pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd3_pred<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb86-2"><a href="#cb86-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb86-3"><a href="#cb86-3" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd3_pred<span class="sc">$</span>ballotposition_new))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd3_pred$ballotposition_new)), &quot;Deselected&quot;,
: NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb88"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb88-1"><a href="#cb88-1" aria-hidden="true" tabindex="-1"></a>pd3_pred<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd3_pred<span class="sc">$</span>ballotposition_new,</span>
<span id="cb88-2"><a href="#cb88-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb88-3"><a href="#cb88-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb88-4"><a href="#cb88-4" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> pd3_pred, <span class="fu">aes</span>(<span class="at">x =</span> lr, </span>
<span id="cb88-5"><a href="#cb88-5" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb88-6"><a href="#cb88-6" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb88-7"><a href="#cb88-7" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb88-8"><a href="#cb88-8" aria-hidden="true" tabindex="-1"></a>                       <span class="at">fill =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>),</span>
<span id="cb88-9"><a href="#cb88-9" aria-hidden="true" tabindex="-1"></a>                       <span class="at">color =</span> <span class="fu">ifelse</span>(fct_gender_Male <span class="sc">==</span> <span class="dv">1</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>))) <span class="sc">+</span></span>
<span id="cb88-10"><a href="#cb88-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span>.<span class="dv">2</span>,.<span class="dv">5</span>,<span class="at">by=</span>.<span class="dv">1</span>), </span>
<span id="cb88-11"><a href="#cb88-11" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb88-12"><a href="#cb88-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb88-13"><a href="#cb88-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb88-14"><a href="#cb88-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_ribbon</span>(<span class="at">alpha =</span> .<span class="dv">5</span>, <span class="at">color =</span> <span class="cn">NA</span>) <span class="sc">+</span></span>
<span id="cb88-15"><a href="#cb88-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>) <span class="sc">+</span></span>
<span id="cb88-16"><a href="#cb88-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_grid</span>(respondent_gender <span class="sc">~</span> ballotposition_new) <span class="sc">+</span></span>
<span id="cb88-17"><a href="#cb88-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Left-Right&quot;</span>) <span class="sc">+</span></span>
<span id="cb88-18"><a href="#cb88-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>) <span class="sc">+</span></span>
<span id="cb88-19"><a href="#cb88-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Probability&quot;</span>) <span class="sc">+</span></span>
<span id="cb88-20"><a href="#cb88-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb88-21"><a href="#cb88-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, </span>
<span id="cb88-22"><a href="#cb88-22" aria-hidden="true" tabindex="-1"></a>                    <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb88-23"><a href="#cb88-23" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb88-24"><a href="#cb88-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="st">&quot;Aspirant&#39;s Gender&quot;</span>, </span>
<span id="cb88-25"><a href="#cb88-25" aria-hidden="true" tabindex="-1"></a>                     <span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;orange&quot;</span>,</span>
<span id="cb88-26"><a href="#cb88-26" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span> </span>
<span id="cb88-27"><a href="#cb88-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb88-28"><a href="#cb88-28" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb88-29"><a href="#cb88-29" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="table-m" class="level2" data-number="6">
<h2 data-number="6" class="anchored" data-anchor-id="table-m"><span class="header-section-number">6</span> TABLE M</h2>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb89"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb89-1"><a href="#cb89-1" aria-hidden="true" tabindex="-1"></a><span class="co"># TABLE APPENDIX M</span></span>
<span id="cb89-2"><a href="#cb89-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb89-3"><a href="#cb89-3" aria-hidden="true" tabindex="-1"></a>texreg<span class="sc">::</span><span class="fu">htmlreg</span>(<span class="fu">list</span>(mod0,mod2,mod1,mod3,mod3m,mod3f),</span>
<span id="cb89-4"><a href="#cb89-4" aria-hidden="true" tabindex="-1"></a>               <span class="at">custom.model.names =</span> <span class="fu">c</span>(<span class="st">&quot;Base&quot;</span>,</span>
<span id="cb89-5"><a href="#cb89-5" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Int. Gender&quot;</span>,</span>
<span id="cb89-6"><a href="#cb89-6" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Int. Supply&quot;</span>,</span>
<span id="cb89-7"><a href="#cb89-7" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Int. LR&quot;</span>,</span>
<span id="cb89-8"><a href="#cb89-8" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Int. LR/Men&quot;</span>,</span>
<span id="cb89-9"><a href="#cb89-9" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Int. LR/Women&quot;</span>),</span>
<span id="cb89-10"><a href="#cb89-10" aria-hidden="true" tabindex="-1"></a>               <span class="at">booktabs =</span> <span class="cn">TRUE</span>, <span class="at">longtable =</span> <span class="cn">TRUE</span>, </span>
<span id="cb89-11"><a href="#cb89-11" aria-hidden="true" tabindex="-1"></a>               <span class="at">caption.above =</span> <span class="cn">TRUE</span>,</span>
<span id="cb89-12"><a href="#cb89-12" aria-hidden="true" tabindex="-1"></a>               <span class="at">fontsize =</span> <span class="st">&quot;tiny&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<table class="texreg" style="margin: 10px auto;border-collapse: collapse;border-spacing: 0px;color: #000000;border-top: 2px solid #000000;">
<caption>
Statistical models
</caption>
<thead>
<tr>
<th style="padding-left: 5px;padding-right: 5px;">
 
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Base
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Int. Gender
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Int. Supply
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Int. LR
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Int. LR/Men
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Int. LR/Women
</th>
</tr>
</thead>
<tbody>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
2: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.70
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.52
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.66
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.59
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.28
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.83)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.53<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.09<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.32
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.87
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.44
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.40
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.54)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.86)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.73
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.24)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.45<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.46<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.45<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.46<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.40<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.68<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.49
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.65
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.65)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.32
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.89
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.70)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.77
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.60
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.60
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.59
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.43
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.25
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.70)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.36
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.18
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.55
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.56
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.48)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.66)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.48
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.49
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.48
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.48
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.73
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.55)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.39
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.12
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.39<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.26
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.15
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.67<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.59
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.75<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.70
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.67
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.79
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.24<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.01
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.80)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.51
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.40
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.12
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.54)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.87)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.49<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.49<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.48<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.48<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.45
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.65
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.36
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.22
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.13
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.83<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.97
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.63)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.23
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.77)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.40
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.40
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.85
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.29
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.48)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.63)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.16
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.38
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.64)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.42
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.68)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.10
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.55)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.36
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.51
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.42
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.42
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.60<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.07<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.07<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.06<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.06<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.21<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.77
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.26)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.11<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.87<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.95<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.54<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.81)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.36<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.03<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.93<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.76
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.28
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.23
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.55)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.85)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.09
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.51<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.38
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.40
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.29
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.29
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.29
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.87<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.33
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.75
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.53
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.65)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.28
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.61
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.72)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.27
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.58
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.22
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.74<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.71<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.78<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.73<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.75
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.72
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.61)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.25
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.59)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.13
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.13
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.48
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.66)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.83<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.80<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.07<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.38
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.22
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.31
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.51<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.51<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.51<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.58<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.34
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.10<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.09<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.09<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.09<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.16<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.96<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.26)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.38<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.35<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.37
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.18<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.18<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.38
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.53)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.79)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.45<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.72<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.24<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.94<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.96
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.65
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.56)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.88)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.76
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.42<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.95<sup>**</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.05
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.55<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.56<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.55<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.55<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.56<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.55
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.64
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.66
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.64
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.82
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.16
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.66)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.51
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.68)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.32
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.29
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.46
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.67<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.37
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.14
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.59)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.39
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.38
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.43
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.47
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.59)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.40
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.63)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.84<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.85<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.86<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.83<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.70
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.46<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.33)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.58
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.59
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.79
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.59)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.22
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.80<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.93<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.47<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.47<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.46<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.46<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.40<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.73<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.26)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.40<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.08<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.74
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.29<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.20
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.55)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.86)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.65<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.47<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.96<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.99<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.47<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.59<sup>**</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.58)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.89)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.43<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.44<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.43<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.43<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.38
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.77
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.24)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.48<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.76<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.33
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.69<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.72<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.69<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.70<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.63<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.86<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.25)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.45
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.46
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.48
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.43
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.88<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.60
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.64)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.38
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.00
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.68)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.98<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.99<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.96<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.97<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.20<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.70
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.69)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.83<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.79<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.90<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.80<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.82
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.68
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.47
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.47
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.43
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.58
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.32
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.36
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.92
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.63)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.31<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.30<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.34<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.30<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.43<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.18
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.60
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.64
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.58
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.79
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.35)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.43)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.63)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.28
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.28
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.27
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.37
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.99<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.99<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.98<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.00<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.16<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.87<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.86<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.87<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.87<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.80<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-2.11<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.26)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: (Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.10<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.86<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.99<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.66<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.26<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.47
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.45)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.50)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.71)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.90<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.59<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.44<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.80<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.68<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.60<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.48)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.49)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.76)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_deviation_sometimes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.20
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.19
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.34
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_deviation_frequently
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.02<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.04<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.02<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.02<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.81<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.72<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_experience_Incumbency
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.70<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.71<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.71<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.72<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.63<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.97<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_position_center
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.32
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_position_rightwing
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.10<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.12<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.09<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.10<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.83<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.85<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.21)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Welfare
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.64<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.99<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_EUForeign
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.15
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.13
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.62
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.96
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.61)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Finance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.56
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.55
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.80<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.55)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Generalist
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.63<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.59<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.68<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.65
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.33
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.49)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Health
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.74<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.74<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.75<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.72<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.97<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.38)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Domestic
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.33
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.57)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Environment
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.22<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.22<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.25<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.21<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.42<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.86
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.48)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_issue_Economy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.54
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.52
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.78<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.14
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_otherlist_Yes
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.42<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.42<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.40<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.55<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.14)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.26)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_personalvotes_moderate
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.04<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.03<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.03<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.04<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.27<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.45
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.20)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.24)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_personalvotes_high
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.77<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.76<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.77<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.77<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.97<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.31<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.27
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.78<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.41
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.34
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.23)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.94<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.37
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.44
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.24)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.16<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.33
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_gender_Male:respondent_gender_Male
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.96<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.35<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.40<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.29<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.23<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_gender_Male:n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.33<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.10)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
2: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.10)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
3: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.09
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.03
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
4: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.05
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.18)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
5: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.10
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.13<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.13
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
6: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.28<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.25
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.11
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.05)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.06)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.10)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deselected: fct_gender_Male:lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.21<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.16)
</td>
</tr>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
AIC
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10369.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10375.78
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10346.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10375.62
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7291.80
</td>
<td style="padding-left: 5px;padding-right: 5px;">
3198.40
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
BIC
</td>
<td style="padding-left: 5px;padding-right: 5px;">
11014.97
</td>
<td style="padding-left: 5px;padding-right: 5px;">
11093.14
</td>
<td style="padding-left: 5px;padding-right: 5px;">
11063.53
</td>
<td style="padding-left: 5px;padding-right: 5px;">
11092.98
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7965.40
</td>
<td style="padding-left: 5px;padding-right: 5px;">
3773.48
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Log Likelihood
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-5076.67
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-5067.89
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-5053.09
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-5067.81
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-3525.90
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1479.20
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deviance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10153.35
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10135.78
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10106.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
10135.62
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7051.80
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2958.40
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Num. obs.
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2916
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2916
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2916
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2916
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2025
</td>
<td style="padding-left: 5px;padding-right: 5px;">
891
</td>
</tr>
<tr style="border-bottom: 2px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
K
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
7
</td>
</tr>
</tbody>
<tfoot>
<tr>
<td style="font-size: 0.8em;" colspan="7">
<sup>***</sup>p &lt; 0.001; <sup>**</sup>p &lt; 0.01; <sup>*</sup>p &lt; 0.05
</td>
</tr>
</tfoot>
</table>
</section>
<section id="fri-figure-a8-figure-4-table-3-table-a3-figure-a4" class="level2" data-number="7">
<h2 data-number="7" class="anchored" data-anchor-id="fri-figure-a8-figure-4-table-3-table-a3-figure-a4"><span class="header-section-number">7</span> FRI: FIGURE A8, FIGURE 4, TABLE 3, TABLE A3, FIGURE A4</h2>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb90"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb90-1"><a href="#cb90-1" aria-hidden="true" tabindex="-1"></a><span class="do">#####################################</span></span>
<span id="cb90-2"><a href="#cb90-2" aria-hidden="true" tabindex="-1"></a><span class="co"># FRI ANALYSIS</span></span>
<span id="cb90-3"><a href="#cb90-3" aria-hidden="true" tabindex="-1"></a><span class="do">#####################################</span></span>
<span id="cb90-4"><a href="#cb90-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-5"><a href="#cb90-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Covariates</span></span>
<span id="cb90-6"><a href="#cb90-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-7"><a href="#cb90-7" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(dplyr)</span>
<span id="cb90-8"><a href="#cb90-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-9"><a href="#cb90-9" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>max_einfluss <span class="ot">&lt;-</span> <span class="fu">apply</span>(dplyr<span class="sc">::</span><span class="fu">select</span>(<span class="fu">ungroup</span>(df),</span>
<span id="cb90-10"><a href="#cb90-10" aria-hidden="true" tabindex="-1"></a>                                <span class="fu">starts_with</span>(<span class="st">&quot;qefficacy&quot;</span>)),</span>
<span id="cb90-11"><a href="#cb90-11" aria-hidden="true" tabindex="-1"></a>                         <span class="dv">1</span>,</span>
<span id="cb90-12"><a href="#cb90-12" aria-hidden="true" tabindex="-1"></a>                         max)</span>
<span id="cb90-13"><a href="#cb90-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-14"><a href="#cb90-14" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>age <span class="ot">&lt;-</span> <span class="dv">2021</span> <span class="sc">-</span> df<span class="sc">$</span>qyob</span>
<span id="cb90-15"><a href="#cb90-15" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-16"><a href="#cb90-16" aria-hidden="true" tabindex="-1"></a><span class="co"># Index creation</span></span>
<span id="cb90-17"><a href="#cb90-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-18"><a href="#cb90-18" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>bp_value_female <span class="ot">&lt;-</span> <span class="dv">7</span> <span class="sc">-</span> <span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition)</span>
<span id="cb90-19"><a href="#cb90-19" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>bp_value_female[df<span class="sc">$</span>fct_gender <span class="sc">==</span> <span class="st">&quot;Male&quot;</span>] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb90-20"><a href="#cb90-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-21"><a href="#cb90-21" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>lr <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(df<span class="sc">$</span>qleftright1)</span>
<span id="cb90-22"><a href="#cb90-22" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb90-23"><a href="#cb90-23" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span></span>
<span id="cb90-24"><a href="#cb90-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(id, max_einfluss, age, </span>
<span id="cb90-25"><a href="#cb90-25" aria-hidden="true" tabindex="-1"></a>           respondent_party, respondent_gender,</span>
<span id="cb90-26"><a href="#cb90-26" aria-hidden="true" tabindex="-1"></a>           qstrategy, lr) <span class="sc">%&gt;%</span></span>
<span id="cb90-27"><a href="#cb90-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">summarise</span>(<span class="at">female_index =</span> <span class="fu">sum</span>(bp_value_female,</span>
<span id="cb90-28"><a href="#cb90-28" aria-hidden="true" tabindex="-1"></a>                               <span class="at">na.rm =</span> <span class="cn">TRUE</span>),</span>
<span id="cb90-29"><a href="#cb90-29" aria-hidden="true" tabindex="-1"></a>            <span class="at">n_women =</span> <span class="fu">sum</span>(fct_gender <span class="sc">==</span> <span class="st">&quot;Female&quot;</span>)) <span class="ot">-&gt;</span> bp_index</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<pre><code>`summarise()` has grouped output by &#39;id&#39;, &#39;max_einfluss&#39;, &#39;age&#39;,
&#39;respondent_party&#39;, &#39;respondent_gender&#39;, &#39;qstrategy&#39;. You can override using
the `.groups` argument.</code></pre>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb92"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb92-1"><a href="#cb92-1" aria-hidden="true" tabindex="-1"></a>expected_values <span class="ot">&lt;-</span> <span class="fu">data.frame</span>(<span class="at">mean =</span> <span class="fu">c</span>(<span class="dv">0</span><span class="sc">:</span><span class="dv">9</span>)<span class="sc">*</span>(<span class="dv">2</span><span class="sc">/</span><span class="dv">3</span>)<span class="sc">*</span><span class="fl">3.5</span>,</span>
<span id="cb92-2"><a href="#cb92-2" aria-hidden="true" tabindex="-1"></a>                              <span class="at">n_women =</span> <span class="dv">0</span><span class="sc">:</span><span class="dv">9</span>)</span>
<span id="cb92-3"><a href="#cb92-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb92-4"><a href="#cb92-4" aria-hidden="true" tabindex="-1"></a>bp_index <span class="ot">&lt;-</span> <span class="fu">left_join</span>(bp_index, expected_values)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<pre><code>Joining with `by = join_by(n_women)`</code></pre>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb94"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb94-1"><a href="#cb94-1" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>fri <span class="ot">&lt;-</span> bp_index<span class="sc">$</span>female_index <span class="sc">-</span> bp_index<span class="sc">$</span>mean</span>
<span id="cb94-2"><a href="#cb94-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb94-3"><a href="#cb94-3" aria-hidden="true" tabindex="-1"></a><span class="co"># plot for appendix</span></span>
<span id="cb94-4"><a href="#cb94-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb94-5"><a href="#cb94-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(bp_index, <span class="fu">aes</span>(<span class="at">x =</span> fri)) <span class="sc">+</span></span>
<span id="cb94-6"><a href="#cb94-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_vline</span>(<span class="fu">aes</span>(<span class="at">xintercept =</span> <span class="dv">0</span>), <span class="at">lty =</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb94-7"><a href="#cb94-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_histogram</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>, <span class="at">fill =</span> <span class="fu">color_fill</span>(<span class="dv">40</span>), <span class="at">bins =</span> <span class="dv">40</span>) <span class="sc">+</span></span>
<span id="cb94-8"><a href="#cb94-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb94-9"><a href="#cb94-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;FRI&quot;</span>) <span class="sc">+</span></span>
<span id="cb94-10"><a href="#cb94-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;N&quot;</span>) <span class="sc">+</span></span>
<span id="cb94-11"><a href="#cb94-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="fu">seq</span>(<span class="sc">-</span><span class="dv">6</span>,<span class="dv">8</span>,<span class="at">by =</span> <span class="dv">2</span>)) <span class="sc">+</span></span>
<span id="cb94-12"><a href="#cb94-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb94-13"><a href="#cb94-13" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb95"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb95-1"><a href="#cb95-1" aria-hidden="true" tabindex="-1"></a><span class="co"># figure 4</span></span>
<span id="cb95-2"><a href="#cb95-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb95-3"><a href="#cb95-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggridges)</span>
<span id="cb95-4"><a href="#cb95-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb95-5"><a href="#cb95-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(bp_index, </span>
<span id="cb95-6"><a href="#cb95-6" aria-hidden="true" tabindex="-1"></a>       <span class="fu">aes</span>(<span class="at">x =</span> fri,</span>
<span id="cb95-7"><a href="#cb95-7" aria-hidden="true" tabindex="-1"></a>           <span class="at">y =</span> respondent_party,</span>
<span id="cb95-8"><a href="#cb95-8" aria-hidden="true" tabindex="-1"></a>           <span class="at">fill =</span> respondent_party,</span>
<span id="cb95-9"><a href="#cb95-9" aria-hidden="true" tabindex="-1"></a>           <span class="at">color =</span> respondent_party)) <span class="sc">+</span></span>
<span id="cb95-10"><a href="#cb95-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_vline</span>(<span class="fu">aes</span>(<span class="at">xintercept =</span> <span class="dv">0</span>), <span class="at">lty =</span> <span class="dv">2</span>, <span class="at">color =</span> <span class="st">&quot;grey50&quot;</span>) <span class="sc">+</span></span>
<span id="cb95-11"><a href="#cb95-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">stat_density_ridges</span>(<span class="at">quantile_lines =</span> <span class="cn">TRUE</span>, </span>
<span id="cb95-12"><a href="#cb95-12" aria-hidden="true" tabindex="-1"></a>                      <span class="at">quantiles =</span> <span class="dv">2</span>,</span>
<span id="cb95-13"><a href="#cb95-13" aria-hidden="true" tabindex="-1"></a>                      <span class="at">alpha =</span> .<span class="dv">3</span>) <span class="sc">+</span>  </span>
<span id="cb95-14"><a href="#cb95-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">14</span>) <span class="sc">+</span></span>
<span id="cb95-15"><a href="#cb95-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="cn">NULL</span>) <span class="sc">+</span></span>
<span id="cb95-16"><a href="#cb95-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;darkgreen&quot;</span>,</span>
<span id="cb95-17"><a href="#cb95-17" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;#e000b7&quot;</span>,</span>
<span id="cb95-18"><a href="#cb95-18" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;darkred&quot;</span>,</span>
<span id="cb95-19"><a href="#cb95-19" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;turquoise&quot;</span>,</span>
<span id="cb95-20"><a href="#cb95-20" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span></span>
<span id="cb95-21"><a href="#cb95-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;darkgreen&quot;</span>,</span>
<span id="cb95-22"><a href="#cb95-22" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;#e000b7&quot;</span>,</span>
<span id="cb95-23"><a href="#cb95-23" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;darkred&quot;</span>,</span>
<span id="cb95-24"><a href="#cb95-24" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;turquoise&quot;</span>,</span>
<span id="cb95-25"><a href="#cb95-25" aria-hidden="true" tabindex="-1"></a>                               <span class="st">&quot;steelblue&quot;</span>)) <span class="sc">+</span></span>
<span id="cb95-26"><a href="#cb95-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>, <span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb95-27"><a href="#cb95-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Female Ranking Index (FRI)&quot;</span>) <span class="sc">+</span></span>
<span id="cb95-28"><a href="#cb95-28" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb95-29"><a href="#cb95-29" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>())</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<pre><code>Picking joint bandwidth of 0.955</code></pre>
<p><img 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb97"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb97-1"><a href="#cb97-1" aria-hidden="true" tabindex="-1"></a><span class="co"># table 3 (ols)</span></span>
<span id="cb97-2"><a href="#cb97-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb97-3"><a href="#cb97-3" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>n_women <span class="ot">&lt;-</span> <span class="fu">factor</span>(bp_index<span class="sc">$</span>n_women)</span>
<span id="cb97-4"><a href="#cb97-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb97-5"><a href="#cb97-5" aria-hidden="true" tabindex="-1"></a>ols1 <span class="ot">&lt;-</span> <span class="fu">lm</span>(fri <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb97-6"><a href="#cb97-6" aria-hidden="true" tabindex="-1"></a>             age <span class="sc">+</span></span>
<span id="cb97-7"><a href="#cb97-7" aria-hidden="true" tabindex="-1"></a>             respondent_party <span class="sc">+</span></span>
<span id="cb97-8"><a href="#cb97-8" aria-hidden="true" tabindex="-1"></a>             qstrategy <span class="sc">+</span></span>
<span id="cb97-9"><a href="#cb97-9" aria-hidden="true" tabindex="-1"></a>             max_einfluss <span class="sc">+</span></span>
<span id="cb97-10"><a href="#cb97-10" aria-hidden="true" tabindex="-1"></a>             n_women,</span>
<span id="cb97-11"><a href="#cb97-11" aria-hidden="true" tabindex="-1"></a>           <span class="at">data =</span> bp_index)</span>
<span id="cb97-12"><a href="#cb97-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb97-13"><a href="#cb97-13" aria-hidden="true" tabindex="-1"></a>ols2 <span class="ot">&lt;-</span> <span class="fu">lm</span>(fri <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb97-14"><a href="#cb97-14" aria-hidden="true" tabindex="-1"></a>             age <span class="sc">+</span></span>
<span id="cb97-15"><a href="#cb97-15" aria-hidden="true" tabindex="-1"></a>             lr <span class="sc">+</span></span>
<span id="cb97-16"><a href="#cb97-16" aria-hidden="true" tabindex="-1"></a>             qstrategy <span class="sc">+</span></span>
<span id="cb97-17"><a href="#cb97-17" aria-hidden="true" tabindex="-1"></a>             max_einfluss <span class="sc">+</span></span>
<span id="cb97-18"><a href="#cb97-18" aria-hidden="true" tabindex="-1"></a>             n_women,</span>
<span id="cb97-19"><a href="#cb97-19" aria-hidden="true" tabindex="-1"></a>           <span class="at">data =</span> bp_index)</span>
<span id="cb97-20"><a href="#cb97-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb97-21"><a href="#cb97-21" aria-hidden="true" tabindex="-1"></a>texreg<span class="sc">::</span><span class="fu">htmlreg</span>(<span class="fu">list</span>(ols1,ols2), </span>
<span id="cb97-22"><a href="#cb97-22" aria-hidden="true" tabindex="-1"></a>               <span class="at">stars =</span> <span class="fu">c</span>(<span class="fl">0.1</span>, .<span class="dv">05</span>, <span class="fl">0.01</span>),</span>
<span id="cb97-23"><a href="#cb97-23" aria-hidden="true" tabindex="-1"></a>               <span class="at">booktabs =</span> <span class="cn">TRUE</span>,</span>
<span id="cb97-24"><a href="#cb97-24" aria-hidden="true" tabindex="-1"></a>               <span class="co">#custom.model.names = c(&quot;Female Score&quot;),</span></span>
<span id="cb97-25"><a href="#cb97-25" aria-hidden="true" tabindex="-1"></a>               <span class="at">caption.above =</span> <span class="cn">TRUE</span>,</span>
<span id="cb97-26"><a href="#cb97-26" aria-hidden="true" tabindex="-1"></a>               <span class="at">caption =</span> <span class="st">&quot;OLS Regression: Explaining Female Friendly Candidate Ranking&quot;</span>,</span>
<span id="cb97-27"><a href="#cb97-27" aria-hidden="true" tabindex="-1"></a>               <span class="at">label =</span> <span class="st">&quot;tab:femfriendly&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<table class="texreg" style="margin: 10px auto;border-collapse: collapse;border-spacing: 0px;color: #000000;border-top: 2px solid #000000;">
<caption>
OLS Regression: Explaining Female Friendly Candidate Ranking
</caption>
<thead>
<tr>
<th style="padding-left: 5px;padding-right: 5px;">
 
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Model 1
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Model 2
</th>
</tr>
</thead>
<tbody>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
(Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.54
</td>
<td style="padding-left: 5px;padding-right: 5px;">
2.28
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.68)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.72)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_genderMale
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.68<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.80<sup>**</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.32)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
age
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyNEOS
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.50)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partySPÖ
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.26<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyÖVP
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.38<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyFPÖ
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-2.57<sup>***</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.64)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
qstrategy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.04
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.05
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
max_einfluss
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.03
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women2
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.27
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.24
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.56)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.58)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women3
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.96
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.79
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.51)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.53)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women4
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.66
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.46
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.51)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.52)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women5
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.19
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.50)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.52)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women6
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.73
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.81
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.51)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.53)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women7
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.52
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.75
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.55)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.57)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women8
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-3.97<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-4.57<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(2.31)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(2.34)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
lr
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.30<sup>***</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
</tr>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
R<sup>2</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Adj. R<sup>2</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.17
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.15
</td>
</tr>
<tr style="border-bottom: 2px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
Num. obs.
</td>
<td style="padding-left: 5px;padding-right: 5px;">
324
</td>
<td style="padding-left: 5px;padding-right: 5px;">
324
</td>
</tr>
</tbody>
<tfoot>
<tr>
<td style="font-size: 0.8em;" colspan="3">
<sup>***</sup>p &lt; 0.01; <sup>**</sup>p &lt; 0.05; <sup>*</sup>p &lt; 0.1
</td>
</tr>
</tfoot>
</table>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb98"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb98-1"><a href="#cb98-1" aria-hidden="true" tabindex="-1"></a><span class="co"># TABLE A3</span></span>
<span id="cb98-2"><a href="#cb98-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb98-3"><a href="#cb98-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(stargazer)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<pre><code>
Please cite as: 

 Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
 R package version 5.2.3. https://CRAN.R-project.org/package=stargazer </code></pre>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb100"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb100-1"><a href="#cb100-1" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>male <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_gender <span class="sc">==</span> <span class="st">&quot;Male&quot;</span>)</span>
<span id="cb100-2"><a href="#cb100-2" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>fpoe <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;FPÖ&quot;</span>)</span>
<span id="cb100-3"><a href="#cb100-3" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>oevp <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;ÖVP&quot;</span>)</span>
<span id="cb100-4"><a href="#cb100-4" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>greens <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;Greens&quot;</span>)</span>
<span id="cb100-5"><a href="#cb100-5" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>spoe <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;SPÖ&quot;</span>)</span>
<span id="cb100-6"><a href="#cb100-6" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>neos <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>respondent_party <span class="sc">==</span> <span class="st">&quot;NEOS&quot;</span>)</span>
<span id="cb100-7"><a href="#cb100-7" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>n_women <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>n_women)</span>
<span id="cb100-8"><a href="#cb100-8" aria-hidden="true" tabindex="-1"></a>bp_index<span class="sc">$</span>lr <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(bp_index<span class="sc">$</span>lr)</span>
<span id="cb100-9"><a href="#cb100-9" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb100-10"><a href="#cb100-10" aria-hidden="true" tabindex="-1"></a>stargazer<span class="sc">::</span><span class="fu">stargazer</span>(<span class="fu">as.data.frame</span>(bp_index), <span class="at">type =</span> <span class="st">&quot;html&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<table style="text-align:center">
<tbody><tr>
<td colspan="6" style="border-bottom: 1px solid black">
</td>
</tr>
<tr>
<td style="text-align:left">
Statistic
</td>
<td>
N
</td>
<td>
Mean
</td>
<td>
St. Dev.
</td>
<td>
Min
</td>
<td>
Max
</td>
</tr>
<tr>
<td colspan="6" style="border-bottom: 1px solid black">
</td>
</tr>
<tr>
<td style="text-align:left">
max_einfluss
</td>
<td>
324
</td>
<td>
4.830
</td>
<td>
1.842
</td>
<td>
1
</td>
<td>
7
</td>
</tr>
<tr>
<td style="text-align:left">
age
</td>
<td>
324
</td>
<td>
51.028
</td>
<td>
12.018
</td>
<td>
20
</td>
<td>
79
</td>
</tr>
<tr>
<td style="text-align:left">
qstrategy
</td>
<td>
324
</td>
<td>
3.068
</td>
<td>
0.856
</td>
<td>
1
</td>
<td>
5
</td>
</tr>
<tr>
<td style="text-align:left">
lr
</td>
<td>
324
</td>
<td>
4.818
</td>
<td>
1.800
</td>
<td>
1
</td>
<td>
10
</td>
</tr>
<tr>
<td style="text-align:left">
female_index
</td>
<td>
324
</td>
<td>
11.725
</td>
<td>
3.689
</td>
<td>
0
</td>
<td>
21
</td>
</tr>
<tr>
<td style="text-align:left">
n_women
</td>
<td>
324
</td>
<td>
4.531
</td>
<td>
1.467
</td>
<td>
1
</td>
<td>
8
</td>
</tr>
<tr>
<td style="text-align:left">
mean
</td>
<td>
324
</td>
<td>
10.572
</td>
<td>
3.422
</td>
<td>
2.333
</td>
<td>
18.667
</td>
</tr>
<tr>
<td style="text-align:left">
fri
</td>
<td>
324
</td>
<td>
1.153
</td>
<td>
2.770
</td>
<td>
-6.333
</td>
<td>
8.000
</td>
</tr>
<tr>
<td style="text-align:left">
male
</td>
<td>
324
</td>
<td>
0.694
</td>
<td>
0.461
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td style="text-align:left">
fpoe
</td>
<td>
324
</td>
<td>
0.059
</td>
<td>
0.235
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td style="text-align:left">
oevp
</td>
<td>
324
</td>
<td>
0.173
</td>
<td>
0.379
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td style="text-align:left">
greens
</td>
<td>
324
</td>
<td>
0.373
</td>
<td>
0.484
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td style="text-align:left">
spoe
</td>
<td>
324
</td>
<td>
0.272
</td>
<td>
0.445
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td style="text-align:left">
neos
</td>
<td>
324
</td>
<td>
0.123
</td>
<td>
0.329
</td>
<td>
0
</td>
<td>
1
</td>
</tr>
<tr>
<td colspan="6" style="border-bottom: 1px solid black">
</td>
</tr>
</tbody></table>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb101"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb101-1"><a href="#cb101-1" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE A4</span></span>
<span id="cb101-2"><a href="#cb101-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb101-3"><a href="#cb101-3" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(bp_index, <span class="fu">aes</span>(<span class="at">x =</span> age)) <span class="sc">+</span></span>
<span id="cb101-4"><a href="#cb101-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_histogram</span>(<span class="at">color =</span> <span class="st">&quot;white&quot;</span>, <span class="at">fill =</span> <span class="fu">color_fill</span>(<span class="dv">30</span>), <span class="at">bins =</span> <span class="dv">30</span>) <span class="sc">+</span></span>
<span id="cb101-5"><a href="#cb101-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb101-6"><a href="#cb101-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;N&quot;</span>) <span class="sc">+</span></span>
<span id="cb101-7"><a href="#cb101-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Age&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" class="img-fluid" width="672"></p>
</section>
<section id="zipper-figure-5-appendix-g-table-4" class="level2" data-number="8">
<h2 data-number="8" class="anchored" data-anchor-id="zipper-figure-5-appendix-g-table-4"><span class="header-section-number">8</span> ZIPPER: FIGURE 5 + APPENDIX G + TABLE 4</h2>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb102"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb102-1"><a href="#cb102-1" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb102-2"><a href="#cb102-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Ranking Patterns: Zipper Analysis</span></span>
<span id="cb102-3"><a href="#cb102-3" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb102-4"><a href="#cb102-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb102-5"><a href="#cb102-5" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span></span>
<span id="cb102-6"><a href="#cb102-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(ballotposition)) <span class="sc">%&gt;%</span></span>
<span id="cb102-7"><a href="#cb102-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">arrange</span>(id, ballotposition) <span class="sc">%&gt;%</span></span>
<span id="cb102-8"><a href="#cb102-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(id) <span class="sc">%&gt;%</span></span>
<span id="cb102-9"><a href="#cb102-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">summarise</span>(<span class="at">pattern =</span> <span class="fu">paste0</span>(fct_gender,</span>
<span id="cb102-10"><a href="#cb102-10" aria-hidden="true" tabindex="-1"></a>                             <span class="at">collapse =</span> <span class="st">&quot;-&quot;</span>)) <span class="ot">-&gt;</span> gender_sequences</span>
<span id="cb102-11"><a href="#cb102-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb102-12"><a href="#cb102-12" aria-hidden="true" tabindex="-1"></a>gender_sequences <span class="ot">&lt;-</span> <span class="fu">left_join</span>(gender_sequences, </span>
<span id="cb102-13"><a href="#cb102-13" aria-hidden="true" tabindex="-1"></a>                              bp_index)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<pre><code>Joining with `by = join_by(id)`</code></pre>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb104"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb104-1"><a href="#cb104-1" aria-hidden="true" tabindex="-1"></a>gender_sequences <span class="sc">%&gt;%</span></span>
<span id="cb104-2"><a href="#cb104-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(pattern) <span class="sc">%&gt;%</span></span>
<span id="cb104-3"><a href="#cb104-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb104-4"><a href="#cb104-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb104-5"><a href="#cb104-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%&gt;%</span></span>
<span id="cb104-6"><a href="#cb104-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>(n <span class="sc">&gt;</span> <span class="dv">4</span>) <span class="ot">-&gt;</span> overall_pattern</span>
<span id="cb104-7"><a href="#cb104-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb104-8"><a href="#cb104-8" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Male&quot;</span>,<span class="st">&quot;M&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb104-9"><a href="#cb104-9" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Female&quot;</span>,<span class="st">&quot;F&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb104-10"><a href="#cb104-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb104-11"><a href="#cb104-11" aria-hidden="true" tabindex="-1"></a><span class="co"># FIGURE 5</span></span>
<span id="cb104-12"><a href="#cb104-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb104-13"><a href="#cb104-13" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(overall_pattern,</span>
<span id="cb104-14"><a href="#cb104-14" aria-hidden="true" tabindex="-1"></a>       <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent),</span>
<span id="cb104-15"><a href="#cb104-15" aria-hidden="true" tabindex="-1"></a>           <span class="at">y =</span> percent,</span>
<span id="cb104-16"><a href="#cb104-16" aria-hidden="true" tabindex="-1"></a>           <span class="at">color =</span> <span class="fu">reorder</span>(pattern, percent))) <span class="sc">+</span></span>
<span id="cb104-17"><a href="#cb104-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">c</span>(<span class="fl">2.5</span>,<span class="dv">5</span>,<span class="fl">7.5</span>,<span class="dv">10</span>),</span>
<span id="cb104-18"><a href="#cb104-18" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>,</span>
<span id="cb104-19"><a href="#cb104-19" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb104-20"><a href="#cb104-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_segment</span>(<span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb104-21"><a href="#cb104-21" aria-hidden="true" tabindex="-1"></a>                   <span class="at">xend =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb104-22"><a href="#cb104-22" aria-hidden="true" tabindex="-1"></a>                   <span class="at">y =</span> <span class="dv">0</span>, </span>
<span id="cb104-23"><a href="#cb104-23" aria-hidden="true" tabindex="-1"></a>                   <span class="at">yend =</span> percent)) <span class="sc">+</span></span>
<span id="cb104-24"><a href="#cb104-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>(<span class="at">size=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb104-25"><a href="#cb104-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb104-26"><a href="#cb104-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Ranking Sequence&quot;</span>) <span class="sc">+</span></span>
<span id="cb104-27"><a href="#cb104-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;% of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb104-28"><a href="#cb104-28" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">14</span>) <span class="sc">+</span></span>
<span id="cb104-29"><a href="#cb104-29" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">rev</span>(<span class="fu">color_fill</span>(<span class="dv">21</span>))) <span class="sc">+</span></span>
<span id="cb104-30"><a href="#cb104-30" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">seq</span>(<span class="dv">0</span>,<span class="fl">12.5</span>,<span class="fl">2.5</span>),</span>
<span id="cb104-31"><a href="#cb104-31" aria-hidden="true" tabindex="-1"></a>                     <span class="at">expand =</span> <span class="fu">expansion</span>(<span class="at">mult =</span> <span class="fu">c</span>(<span class="dv">0</span>, .<span class="dv">1</span>)),</span>
<span id="cb104-32"><a href="#cb104-32" aria-hidden="true" tabindex="-1"></a>                     <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">&quot;0&quot;</span>,<span class="st">&quot;2.5&quot;</span>,<span class="st">&quot;5&quot;</span>,</span>
<span id="cb104-33"><a href="#cb104-33" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;7.5&quot;</span>, <span class="st">&quot;10&quot;</span>, <span class="st">&quot;12.5&quot;</span>)) <span class="sc">+</span></span>
<span id="cb104-34"><a href="#cb104-34" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb104-35"><a href="#cb104-35" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb104-36"><a href="#cb104-36" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>, <span class="at">fill =</span> <span class="st">&quot;none&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img src="data:image/png;base64,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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb105"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb105-1"><a href="#cb105-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Ranking By Party (for Appendix G)</span></span>
<span id="cb105-2"><a href="#cb105-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-3"><a href="#cb105-3" aria-hidden="true" tabindex="-1"></a>gender_sequences <span class="sc">%&gt;%</span></span>
<span id="cb105-4"><a href="#cb105-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(pattern, respondent_party) <span class="sc">%&gt;%</span></span>
<span id="cb105-5"><a href="#cb105-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb105-6"><a href="#cb105-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(respondent_party) <span class="sc">%&gt;%</span></span>
<span id="cb105-7"><a href="#cb105-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="ot">-&gt;</span> overall_pattern</span>
<span id="cb105-8"><a href="#cb105-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-9"><a href="#cb105-9" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Male&quot;</span>,<span class="st">&quot;M&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb105-10"><a href="#cb105-10" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Female&quot;</span>,<span class="st">&quot;F&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb105-11"><a href="#cb105-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-12"><a href="#cb105-12" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb105-13"><a href="#cb105-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-14"><a href="#cb105-14" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(i <span class="cf">in</span> <span class="fu">unique</span>(overall_pattern<span class="sc">$</span>respondent_party)){</span>
<span id="cb105-15"><a href="#cb105-15" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-16"><a href="#cb105-16" aria-hidden="true" tabindex="-1"></a>  op_x <span class="ot">&lt;-</span> <span class="fu">filter</span>(overall_pattern, respondent_party <span class="sc">==</span> i)</span>
<span id="cb105-17"><a href="#cb105-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-18"><a href="#cb105-18" aria-hidden="true" tabindex="-1"></a>  max_lim <span class="ot">&lt;-</span> <span class="fu">floor</span>(<span class="fu">max</span>(op_x<span class="sc">$</span>percent)) <span class="sc">+</span><span class="dv">2</span></span>
<span id="cb105-19"><a href="#cb105-19" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb105-20"><a href="#cb105-20" aria-hidden="true" tabindex="-1"></a>  ncolors <span class="ot">&lt;-</span> <span class="fu">nrow</span>(op_x)</span>
<span id="cb105-21"><a href="#cb105-21" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb105-22"><a href="#cb105-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(op_x,</span>
<span id="cb105-23"><a href="#cb105-23" aria-hidden="true" tabindex="-1"></a>       <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent),</span>
<span id="cb105-24"><a href="#cb105-24" aria-hidden="true" tabindex="-1"></a>           <span class="at">y =</span> percent,</span>
<span id="cb105-25"><a href="#cb105-25" aria-hidden="true" tabindex="-1"></a>           <span class="at">color =</span> <span class="fu">reorder</span>(pattern, percent))) <span class="sc">+</span></span>
<span id="cb105-26"><a href="#cb105-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="at">by =</span> <span class="dv">2</span>),</span>
<span id="cb105-27"><a href="#cb105-27" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>,</span>
<span id="cb105-28"><a href="#cb105-28" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb105-29"><a href="#cb105-29" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_segment</span>(<span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb105-30"><a href="#cb105-30" aria-hidden="true" tabindex="-1"></a>                   <span class="at">xend =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb105-31"><a href="#cb105-31" aria-hidden="true" tabindex="-1"></a>                   <span class="at">y =</span> <span class="dv">0</span>, </span>
<span id="cb105-32"><a href="#cb105-32" aria-hidden="true" tabindex="-1"></a>                   <span class="at">yend =</span> percent)) <span class="sc">+</span></span>
<span id="cb105-33"><a href="#cb105-33" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>(<span class="at">size=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb105-34"><a href="#cb105-34" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb105-35"><a href="#cb105-35" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Ranking Sequence&quot;</span>) <span class="sc">+</span></span>
<span id="cb105-36"><a href="#cb105-36" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;% of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb105-37"><a href="#cb105-37" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">14</span>) <span class="sc">+</span></span>
<span id="cb105-38"><a href="#cb105-38" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">rev</span>(<span class="fu">color_fill</span>(ncolors))) <span class="sc">+</span></span>
<span id="cb105-39"><a href="#cb105-39" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="dv">2</span>),</span>
<span id="cb105-40"><a href="#cb105-40" aria-hidden="true" tabindex="-1"></a>                     <span class="at">expand =</span> <span class="fu">expansion</span>(<span class="at">mult =</span> <span class="fu">c</span>(<span class="dv">0</span>, .<span class="dv">1</span>))) <span class="sc">+</span></span>
<span id="cb105-41"><a href="#cb105-41" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb105-42"><a href="#cb105-42" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb105-43"><a href="#cb105-43" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>, <span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb105-44"><a href="#cb105-44" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span> respondent_party) <span class="ot">-&gt;</span> p</span>
<span id="cb105-45"><a href="#cb105-45" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-46"><a href="#cb105-46" aria-hidden="true" tabindex="-1"></a>  <span class="fu">print</span>(p)</span>
<span id="cb105-47"><a href="#cb105-47" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb105-48"><a href="#cb105-48" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb105-49"><a href="#cb105-49" aria-hidden="true" tabindex="-1"></a>}</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" 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" 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" 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" 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb106"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb106-1"><a href="#cb106-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Ranking By Gender (for appendix)</span></span>
<span id="cb106-2"><a href="#cb106-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb106-3"><a href="#cb106-3" aria-hidden="true" tabindex="-1"></a>gender_sequences <span class="sc">%&gt;%</span></span>
<span id="cb106-4"><a href="#cb106-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(pattern, respondent_gender) <span class="sc">%&gt;%</span></span>
<span id="cb106-5"><a href="#cb106-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb106-6"><a href="#cb106-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(respondent_gender) <span class="sc">%&gt;%</span></span>
<span id="cb106-7"><a href="#cb106-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="ot">-&gt;</span> overall_pattern</span>
<span id="cb106-8"><a href="#cb106-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb106-9"><a href="#cb106-9" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Male&quot;</span>,<span class="st">&quot;M&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb106-10"><a href="#cb106-10" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Female&quot;</span>,<span class="st">&quot;F&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb106-11"><a href="#cb106-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb106-12"><a href="#cb106-12" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb106-13"><a href="#cb106-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb106-14"><a href="#cb106-14" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(i <span class="cf">in</span> <span class="fu">unique</span>(overall_pattern<span class="sc">$</span>respondent_gender)){</span>
<span id="cb106-15"><a href="#cb106-15" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb106-16"><a href="#cb106-16" aria-hidden="true" tabindex="-1"></a>  op_x <span class="ot">&lt;-</span> <span class="fu">filter</span>(overall_pattern, respondent_gender <span class="sc">==</span> i)</span>
<span id="cb106-17"><a href="#cb106-17" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb106-18"><a href="#cb106-18" aria-hidden="true" tabindex="-1"></a>  max_lim <span class="ot">&lt;-</span> <span class="fu">floor</span>(<span class="fu">max</span>(op_x<span class="sc">$</span>percent)) <span class="sc">+</span><span class="dv">2</span></span>
<span id="cb106-19"><a href="#cb106-19" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb106-20"><a href="#cb106-20" aria-hidden="true" tabindex="-1"></a>  ncolors <span class="ot">&lt;-</span> <span class="fu">nrow</span>(op_x)</span>
<span id="cb106-21"><a href="#cb106-21" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb106-22"><a href="#cb106-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(op_x,</span>
<span id="cb106-23"><a href="#cb106-23" aria-hidden="true" tabindex="-1"></a>         <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent),</span>
<span id="cb106-24"><a href="#cb106-24" aria-hidden="true" tabindex="-1"></a>             <span class="at">y =</span> percent,</span>
<span id="cb106-25"><a href="#cb106-25" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="fu">reorder</span>(pattern, percent))) <span class="sc">+</span></span>
<span id="cb106-26"><a href="#cb106-26" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="at">by =</span> <span class="dv">2</span>),</span>
<span id="cb106-27"><a href="#cb106-27" aria-hidden="true" tabindex="-1"></a>               <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>,</span>
<span id="cb106-28"><a href="#cb106-28" aria-hidden="true" tabindex="-1"></a>               <span class="at">lty =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb106-29"><a href="#cb106-29" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_segment</span>(<span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb106-30"><a href="#cb106-30" aria-hidden="true" tabindex="-1"></a>                     <span class="at">xend =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb106-31"><a href="#cb106-31" aria-hidden="true" tabindex="-1"></a>                     <span class="at">y =</span> <span class="dv">0</span>, </span>
<span id="cb106-32"><a href="#cb106-32" aria-hidden="true" tabindex="-1"></a>                     <span class="at">yend =</span> percent)) <span class="sc">+</span></span>
<span id="cb106-33"><a href="#cb106-33" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">size=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb106-34"><a href="#cb106-34" aria-hidden="true" tabindex="-1"></a>    <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb106-35"><a href="#cb106-35" aria-hidden="true" tabindex="-1"></a>    <span class="fu">xlab</span>(<span class="st">&quot;Ranking Sequence&quot;</span>) <span class="sc">+</span></span>
<span id="cb106-36"><a href="#cb106-36" aria-hidden="true" tabindex="-1"></a>    <span class="fu">ylab</span>(<span class="st">&quot;% of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb106-37"><a href="#cb106-37" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">14</span>) <span class="sc">+</span></span>
<span id="cb106-38"><a href="#cb106-38" aria-hidden="true" tabindex="-1"></a>    <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">rev</span>(<span class="fu">color_fill</span>(ncolors))) <span class="sc">+</span></span>
<span id="cb106-39"><a href="#cb106-39" aria-hidden="true" tabindex="-1"></a>    <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="dv">2</span>),</span>
<span id="cb106-40"><a href="#cb106-40" aria-hidden="true" tabindex="-1"></a>                       <span class="at">expand =</span> <span class="fu">expansion</span>(<span class="at">mult =</span> <span class="fu">c</span>(<span class="dv">0</span>, .<span class="dv">1</span>))) <span class="sc">+</span></span>
<span id="cb106-41"><a href="#cb106-41" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb106-42"><a href="#cb106-42" aria-hidden="true" tabindex="-1"></a>          <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb106-43"><a href="#cb106-43" aria-hidden="true" tabindex="-1"></a>    <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>, <span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb106-44"><a href="#cb106-44" aria-hidden="true" tabindex="-1"></a>    <span class="fu">facet_wrap</span>(<span class="sc">~</span> respondent_gender) <span class="ot">-&gt;</span> p</span>
<span id="cb106-45"><a href="#cb106-45" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb106-46"><a href="#cb106-46" aria-hidden="true" tabindex="-1"></a>  <span class="fu">print</span>(p)</span>
<span id="cb106-47"><a href="#cb106-47" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb106-48"><a href="#cb106-48" aria-hidden="true" tabindex="-1"></a>}</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img src="data:image/png;base64,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" 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb107"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb107-1"><a href="#cb107-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Ranking By Supply (for appendix)</span></span>
<span id="cb107-2"><a href="#cb107-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-3"><a href="#cb107-3" aria-hidden="true" tabindex="-1"></a>gender_sequences<span class="sc">$</span>supply_cat <span class="ot">&lt;-</span> <span class="fu">case_when</span>(gender_sequences<span class="sc">$</span>n_women <span class="sc">&lt;</span> <span class="dv">4</span> <span class="sc">~</span> <span class="st">&quot;less than 4 women&quot;</span>,</span>
<span id="cb107-4"><a href="#cb107-4" aria-hidden="true" tabindex="-1"></a>                                         gender_sequences<span class="sc">$</span>n_women <span class="sc">&gt;</span> <span class="dv">5</span> <span class="sc">~</span> <span class="st">&quot;more than 5 women&quot;</span>,</span>
<span id="cb107-5"><a href="#cb107-5" aria-hidden="true" tabindex="-1"></a>                                         <span class="cn">TRUE</span> <span class="sc">~</span> <span class="st">&quot;4 or 5 women&quot;</span>)</span>
<span id="cb107-6"><a href="#cb107-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-7"><a href="#cb107-7" aria-hidden="true" tabindex="-1"></a>gender_sequences <span class="sc">%&gt;%</span></span>
<span id="cb107-8"><a href="#cb107-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(pattern, supply_cat) <span class="sc">%&gt;%</span></span>
<span id="cb107-9"><a href="#cb107-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb107-10"><a href="#cb107-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(supply_cat) <span class="sc">%&gt;%</span></span>
<span id="cb107-11"><a href="#cb107-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="ot">-&gt;</span> overall_pattern</span>
<span id="cb107-12"><a href="#cb107-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-13"><a href="#cb107-13" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Male&quot;</span>,<span class="st">&quot;M&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb107-14"><a href="#cb107-14" aria-hidden="true" tabindex="-1"></a>overall_pattern<span class="sc">$</span>pattern <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;Female&quot;</span>,<span class="st">&quot;F&quot;</span>,overall_pattern<span class="sc">$</span>pattern)</span>
<span id="cb107-15"><a href="#cb107-15" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-16"><a href="#cb107-16" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb107-17"><a href="#cb107-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-18"><a href="#cb107-18" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(i <span class="cf">in</span> <span class="fu">unique</span>(overall_pattern<span class="sc">$</span>supply_cat)){</span>
<span id="cb107-19"><a href="#cb107-19" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb107-20"><a href="#cb107-20" aria-hidden="true" tabindex="-1"></a>  op_x <span class="ot">&lt;-</span> <span class="fu">filter</span>(overall_pattern, supply_cat <span class="sc">==</span> i)</span>
<span id="cb107-21"><a href="#cb107-21" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb107-22"><a href="#cb107-22" aria-hidden="true" tabindex="-1"></a>  max_lim <span class="ot">&lt;-</span> <span class="fu">floor</span>(<span class="fu">max</span>(op_x<span class="sc">$</span>percent)) <span class="sc">+</span><span class="dv">2</span></span>
<span id="cb107-23"><a href="#cb107-23" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb107-24"><a href="#cb107-24" aria-hidden="true" tabindex="-1"></a>  ncolors <span class="ot">&lt;-</span> <span class="fu">nrow</span>(op_x)</span>
<span id="cb107-25"><a href="#cb107-25" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb107-26"><a href="#cb107-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(op_x,</span>
<span id="cb107-27"><a href="#cb107-27" aria-hidden="true" tabindex="-1"></a>         <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent),</span>
<span id="cb107-28"><a href="#cb107-28" aria-hidden="true" tabindex="-1"></a>             <span class="at">y =</span> percent,</span>
<span id="cb107-29"><a href="#cb107-29" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="fu">reorder</span>(pattern, percent))) <span class="sc">+</span></span>
<span id="cb107-30"><a href="#cb107-30" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="at">by =</span> <span class="dv">2</span>),</span>
<span id="cb107-31"><a href="#cb107-31" aria-hidden="true" tabindex="-1"></a>               <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>,</span>
<span id="cb107-32"><a href="#cb107-32" aria-hidden="true" tabindex="-1"></a>               <span class="at">lty =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb107-33"><a href="#cb107-33" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_segment</span>(<span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb107-34"><a href="#cb107-34" aria-hidden="true" tabindex="-1"></a>                     <span class="at">xend =</span> <span class="fu">reorder</span>(pattern, percent), </span>
<span id="cb107-35"><a href="#cb107-35" aria-hidden="true" tabindex="-1"></a>                     <span class="at">y =</span> <span class="dv">0</span>, </span>
<span id="cb107-36"><a href="#cb107-36" aria-hidden="true" tabindex="-1"></a>                     <span class="at">yend =</span> percent)) <span class="sc">+</span></span>
<span id="cb107-37"><a href="#cb107-37" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">size=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb107-38"><a href="#cb107-38" aria-hidden="true" tabindex="-1"></a>    <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb107-39"><a href="#cb107-39" aria-hidden="true" tabindex="-1"></a>    <span class="fu">xlab</span>(<span class="st">&quot;Ranking Sequence&quot;</span>) <span class="sc">+</span></span>
<span id="cb107-40"><a href="#cb107-40" aria-hidden="true" tabindex="-1"></a>    <span class="fu">ylab</span>(<span class="st">&quot;% of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb107-41"><a href="#cb107-41" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">14</span>) <span class="sc">+</span></span>
<span id="cb107-42"><a href="#cb107-42" aria-hidden="true" tabindex="-1"></a>    <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">rev</span>(<span class="fu">color_fill</span>(ncolors))) <span class="sc">+</span></span>
<span id="cb107-43"><a href="#cb107-43" aria-hidden="true" tabindex="-1"></a>    <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">seq</span>(<span class="dv">0</span>,max_lim,<span class="dv">2</span>),</span>
<span id="cb107-44"><a href="#cb107-44" aria-hidden="true" tabindex="-1"></a>                       <span class="at">expand =</span> <span class="fu">expansion</span>(<span class="at">mult =</span> <span class="fu">c</span>(<span class="dv">0</span>, .<span class="dv">1</span>))) <span class="sc">+</span></span>
<span id="cb107-45"><a href="#cb107-45" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb107-46"><a href="#cb107-46" aria-hidden="true" tabindex="-1"></a>          <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb107-47"><a href="#cb107-47" aria-hidden="true" tabindex="-1"></a>    <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>, <span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb107-48"><a href="#cb107-48" aria-hidden="true" tabindex="-1"></a>    <span class="fu">facet_wrap</span>(<span class="sc">~</span> supply_cat) <span class="ot">-&gt;</span> p</span>
<span id="cb107-49"><a href="#cb107-49" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb107-50"><a href="#cb107-50" aria-hidden="true" tabindex="-1"></a>  <span class="fu">print</span>(p)</span>
<span id="cb107-51"><a href="#cb107-51" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb107-52"><a href="#cb107-52" aria-hidden="true" tabindex="-1"></a>}</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" 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" 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb108"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb108-1"><a href="#cb108-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Regression analysis ZIPPER (TABLE 4)</span></span>
<span id="cb108-2"><a href="#cb108-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-3"><a href="#cb108-3" aria-hidden="true" tabindex="-1"></a>foranalysis <span class="ot">&lt;-</span> <span class="fu">filter</span>(gender_sequences, n_women <span class="sc">&gt;=</span> <span class="dv">3</span> <span class="sc">&amp;</span> n_women <span class="sc">&lt;=</span> <span class="dv">6</span>)</span>
<span id="cb108-4"><a href="#cb108-4" aria-hidden="true" tabindex="-1"></a>foranalysis2 <span class="ot">&lt;-</span> <span class="fu">filter</span>(gender_sequences, n_women <span class="sc">&gt;=</span> <span class="dv">2</span> <span class="sc">&amp;</span> n_women <span class="sc">&lt;=</span> <span class="dv">7</span>)</span>
<span id="cb108-5"><a href="#cb108-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-6"><a href="#cb108-6" aria-hidden="true" tabindex="-1"></a>mz <span class="ot">&lt;-</span> <span class="st">&quot;Male-Female-Male-Female-Male-Female&quot;</span></span>
<span id="cb108-7"><a href="#cb108-7" aria-hidden="true" tabindex="-1"></a>fz <span class="ot">&lt;-</span> <span class="st">&quot;Female-Male-Female-Male-Female-Male&quot;</span></span>
<span id="cb108-8"><a href="#cb108-8" aria-hidden="true" tabindex="-1"></a>mz2 <span class="ot">&lt;-</span> <span class="st">&quot;^Male-Female-Male-Female.*&quot;</span></span>
<span id="cb108-9"><a href="#cb108-9" aria-hidden="true" tabindex="-1"></a>fz2 <span class="ot">&lt;-</span> <span class="st">&quot;^Female-Male-Female-Male.*&quot;</span></span>
<span id="cb108-10"><a href="#cb108-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-11"><a href="#cb108-11" aria-hidden="true" tabindex="-1"></a>foranalysis<span class="sc">$</span>female_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(foranalysis<span class="sc">$</span>pattern <span class="sc">==</span> fz)</span>
<span id="cb108-12"><a href="#cb108-12" aria-hidden="true" tabindex="-1"></a>foranalysis<span class="sc">$</span>male_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(foranalysis<span class="sc">$</span>pattern <span class="sc">==</span> mz)</span>
<span id="cb108-13"><a href="#cb108-13" aria-hidden="true" tabindex="-1"></a>foranalysis<span class="sc">$</span>any_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(foranalysis<span class="sc">$</span>pattern <span class="sc">==</span> mz <span class="sc">|</span> foranalysis<span class="sc">$</span>pattern <span class="sc">==</span> fz)</span>
<span id="cb108-14"><a href="#cb108-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-15"><a href="#cb108-15" aria-hidden="true" tabindex="-1"></a>foranalysis2<span class="sc">$</span>female_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(<span class="fu">grepl</span>(fz2, foranalysis2<span class="sc">$</span>pattern))</span>
<span id="cb108-16"><a href="#cb108-16" aria-hidden="true" tabindex="-1"></a>foranalysis2<span class="sc">$</span>male_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(<span class="fu">grepl</span>(mz2, foranalysis2<span class="sc">$</span>pattern))</span>
<span id="cb108-17"><a href="#cb108-17" aria-hidden="true" tabindex="-1"></a>foranalysis2<span class="sc">$</span>any_zipper <span class="ot">&lt;-</span> <span class="fu">as.numeric</span>(<span class="fu">grepl</span>(fz2, foranalysis2<span class="sc">$</span>pattern) <span class="sc">|</span> <span class="fu">grepl</span>(mz2, foranalysis2<span class="sc">$</span>pattern))</span>
<span id="cb108-18"><a href="#cb108-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-19"><a href="#cb108-19" aria-hidden="true" tabindex="-1"></a>logit1a <span class="ot">&lt;-</span> <span class="fu">glm</span>(female_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-20"><a href="#cb108-20" aria-hidden="true" tabindex="-1"></a>                 age <span class="sc">+</span></span>
<span id="cb108-21"><a href="#cb108-21" aria-hidden="true" tabindex="-1"></a>                 respondent_party <span class="sc">+</span></span>
<span id="cb108-22"><a href="#cb108-22" aria-hidden="true" tabindex="-1"></a>                 qstrategy <span class="sc">+</span></span>
<span id="cb108-23"><a href="#cb108-23" aria-hidden="true" tabindex="-1"></a>                 max_einfluss <span class="sc">+</span></span>
<span id="cb108-24"><a href="#cb108-24" aria-hidden="true" tabindex="-1"></a>                 n_women,</span>
<span id="cb108-25"><a href="#cb108-25" aria-hidden="true" tabindex="-1"></a>               <span class="at">data =</span> foranalysis2,</span>
<span id="cb108-26"><a href="#cb108-26" aria-hidden="true" tabindex="-1"></a>               <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-27"><a href="#cb108-27" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-28"><a href="#cb108-28" aria-hidden="true" tabindex="-1"></a>logit2a <span class="ot">&lt;-</span> <span class="fu">glm</span>(male_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-29"><a href="#cb108-29" aria-hidden="true" tabindex="-1"></a>                 age <span class="sc">+</span></span>
<span id="cb108-30"><a href="#cb108-30" aria-hidden="true" tabindex="-1"></a>                 respondent_party <span class="sc">+</span></span>
<span id="cb108-31"><a href="#cb108-31" aria-hidden="true" tabindex="-1"></a>                 qstrategy <span class="sc">+</span></span>
<span id="cb108-32"><a href="#cb108-32" aria-hidden="true" tabindex="-1"></a>                 max_einfluss <span class="sc">+</span></span>
<span id="cb108-33"><a href="#cb108-33" aria-hidden="true" tabindex="-1"></a>                 n_women,</span>
<span id="cb108-34"><a href="#cb108-34" aria-hidden="true" tabindex="-1"></a>               <span class="at">data =</span> foranalysis2,</span>
<span id="cb108-35"><a href="#cb108-35" aria-hidden="true" tabindex="-1"></a>               <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-36"><a href="#cb108-36" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-37"><a href="#cb108-37" aria-hidden="true" tabindex="-1"></a>logit3a <span class="ot">&lt;-</span> <span class="fu">glm</span>(any_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-38"><a href="#cb108-38" aria-hidden="true" tabindex="-1"></a>                 age <span class="sc">+</span></span>
<span id="cb108-39"><a href="#cb108-39" aria-hidden="true" tabindex="-1"></a>                 respondent_party <span class="sc">+</span></span>
<span id="cb108-40"><a href="#cb108-40" aria-hidden="true" tabindex="-1"></a>                 qstrategy <span class="sc">+</span></span>
<span id="cb108-41"><a href="#cb108-41" aria-hidden="true" tabindex="-1"></a>                 max_einfluss <span class="sc">+</span></span>
<span id="cb108-42"><a href="#cb108-42" aria-hidden="true" tabindex="-1"></a>                 n_women,</span>
<span id="cb108-43"><a href="#cb108-43" aria-hidden="true" tabindex="-1"></a>               <span class="at">data =</span> foranalysis2,</span>
<span id="cb108-44"><a href="#cb108-44" aria-hidden="true" tabindex="-1"></a>               <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-45"><a href="#cb108-45" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-46"><a href="#cb108-46" aria-hidden="true" tabindex="-1"></a>logit1 <span class="ot">&lt;-</span> <span class="fu">glm</span>(female_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-47"><a href="#cb108-47" aria-hidden="true" tabindex="-1"></a>                age <span class="sc">+</span></span>
<span id="cb108-48"><a href="#cb108-48" aria-hidden="true" tabindex="-1"></a>                respondent_party <span class="sc">+</span></span>
<span id="cb108-49"><a href="#cb108-49" aria-hidden="true" tabindex="-1"></a>                qstrategy <span class="sc">+</span></span>
<span id="cb108-50"><a href="#cb108-50" aria-hidden="true" tabindex="-1"></a>                max_einfluss <span class="sc">+</span></span>
<span id="cb108-51"><a href="#cb108-51" aria-hidden="true" tabindex="-1"></a>                n_women,</span>
<span id="cb108-52"><a href="#cb108-52" aria-hidden="true" tabindex="-1"></a>              <span class="at">data =</span> foranalysis,</span>
<span id="cb108-53"><a href="#cb108-53" aria-hidden="true" tabindex="-1"></a>              <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-54"><a href="#cb108-54" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-55"><a href="#cb108-55" aria-hidden="true" tabindex="-1"></a>logit2 <span class="ot">&lt;-</span> <span class="fu">glm</span>(male_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-56"><a href="#cb108-56" aria-hidden="true" tabindex="-1"></a>                age <span class="sc">+</span></span>
<span id="cb108-57"><a href="#cb108-57" aria-hidden="true" tabindex="-1"></a>                respondent_party <span class="sc">+</span></span>
<span id="cb108-58"><a href="#cb108-58" aria-hidden="true" tabindex="-1"></a>                qstrategy <span class="sc">+</span></span>
<span id="cb108-59"><a href="#cb108-59" aria-hidden="true" tabindex="-1"></a>                max_einfluss <span class="sc">+</span></span>
<span id="cb108-60"><a href="#cb108-60" aria-hidden="true" tabindex="-1"></a>                n_women,</span>
<span id="cb108-61"><a href="#cb108-61" aria-hidden="true" tabindex="-1"></a>              <span class="at">data =</span> foranalysis,</span>
<span id="cb108-62"><a href="#cb108-62" aria-hidden="true" tabindex="-1"></a>              <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-63"><a href="#cb108-63" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-64"><a href="#cb108-64" aria-hidden="true" tabindex="-1"></a>logit3 <span class="ot">&lt;-</span> <span class="fu">glm</span>(any_zipper <span class="sc">~</span> respondent_gender <span class="sc">+</span></span>
<span id="cb108-65"><a href="#cb108-65" aria-hidden="true" tabindex="-1"></a>                age <span class="sc">+</span></span>
<span id="cb108-66"><a href="#cb108-66" aria-hidden="true" tabindex="-1"></a>                respondent_party <span class="sc">+</span></span>
<span id="cb108-67"><a href="#cb108-67" aria-hidden="true" tabindex="-1"></a>                qstrategy <span class="sc">+</span></span>
<span id="cb108-68"><a href="#cb108-68" aria-hidden="true" tabindex="-1"></a>                max_einfluss <span class="sc">+</span></span>
<span id="cb108-69"><a href="#cb108-69" aria-hidden="true" tabindex="-1"></a>                n_women,</span>
<span id="cb108-70"><a href="#cb108-70" aria-hidden="true" tabindex="-1"></a>              <span class="at">data =</span> foranalysis,</span>
<span id="cb108-71"><a href="#cb108-71" aria-hidden="true" tabindex="-1"></a>              <span class="at">family =</span> <span class="fu">binomial</span>(<span class="st">&quot;logit&quot;</span>))</span>
<span id="cb108-72"><a href="#cb108-72" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb108-73"><a href="#cb108-73" aria-hidden="true" tabindex="-1"></a>texreg<span class="sc">::</span><span class="fu">htmlreg</span>(<span class="fu">list</span>(logit1, logit2, logit3,</span>
<span id="cb108-74"><a href="#cb108-74" aria-hidden="true" tabindex="-1"></a>                    logit1a, logit2a,logit3a), </span>
<span id="cb108-75"><a href="#cb108-75" aria-hidden="true" tabindex="-1"></a>               <span class="at">stars =</span> <span class="fu">c</span>(<span class="fl">0.1</span>, .<span class="dv">05</span>),</span>
<span id="cb108-76"><a href="#cb108-76" aria-hidden="true" tabindex="-1"></a>               <span class="at">booktabs =</span> <span class="cn">TRUE</span>,</span>
<span id="cb108-77"><a href="#cb108-77" aria-hidden="true" tabindex="-1"></a>               <span class="at">custom.model.names =</span> <span class="fu">c</span>(<span class="st">&quot;&#39;Female&#39; Zipper&quot;</span>,</span>
<span id="cb108-78"><a href="#cb108-78" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;&#39;Male&#39; Zipper&quot;</span>,</span>
<span id="cb108-79"><a href="#cb108-79" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Any Zipper&quot;</span>,</span>
<span id="cb108-80"><a href="#cb108-80" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;&#39;Female&#39; Zipper&quot;</span>,</span>
<span id="cb108-81"><a href="#cb108-81" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;&#39;Male&#39; Zipper&quot;</span>,</span>
<span id="cb108-82"><a href="#cb108-82" aria-hidden="true" tabindex="-1"></a>                                      <span class="st">&quot;Any Zipper&quot;</span>),</span>
<span id="cb108-83"><a href="#cb108-83" aria-hidden="true" tabindex="-1"></a>               <span class="at">caption.above =</span> <span class="cn">TRUE</span>,</span>
<span id="cb108-84"><a href="#cb108-84" aria-hidden="true" tabindex="-1"></a>               <span class="at">caption =</span> <span class="st">&quot;Logistic Regressions: Explaining Zipper Ranking&quot;</span>,</span>
<span id="cb108-85"><a href="#cb108-85" aria-hidden="true" tabindex="-1"></a>               <span class="at">label =</span> <span class="st">&quot;tab:zipper&quot;</span>,</span>
<span id="cb108-86"><a href="#cb108-86" aria-hidden="true" tabindex="-1"></a>               <span class="at">dcolumn =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<table class="texreg" style="margin: 10px auto;border-collapse: collapse;border-spacing: 0px;color: #000000;border-top: 2px solid #000000;">
<caption>
Logistic Regressions: Explaining Zipper Ranking
</caption>
<thead>
<tr>
<th style="padding-left: 5px;padding-right: 5px;">
 
</th>
<th style="padding-left: 5px;padding-right: 5px;">
‘Female’ Zipper
</th>
<th style="padding-left: 5px;padding-right: 5px;">
‘Male’ Zipper
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Any Zipper
</th>
<th style="padding-left: 5px;padding-right: 5px;">
‘Female’ Zipper
</th>
<th style="padding-left: 5px;padding-right: 5px;">
‘Male’ Zipper
</th>
<th style="padding-left: 5px;padding-right: 5px;">
Any Zipper
</th>
</tr>
</thead>
<tbody>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
(Intercept)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.39
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-3.73<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.68
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.95
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-3.48<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.69)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(2.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.39)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.27)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.93)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_genderMale
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.71<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.21<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.53<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.09
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.42)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.66)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.37)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.27)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
age
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.01
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.02
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.02)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.02)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.01)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyNEOS
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.00<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.33
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.75
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.06
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.60)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.85)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.52)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.47)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.56)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.41)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partySPÖ
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.13
</td>
<td style="padding-left: 5px;padding-right: 5px;">
1.35<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.75<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.21
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.65<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.55<sup>*</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.49)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.62)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.40)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.34)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.39)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyÖVP
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.50
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.33
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.23
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.24
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.00
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.73)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.92)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.59)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.44)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.46)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.36)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
respondent_partyFPÖ
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-15.18
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.93
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.43
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.49
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-1.08
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1051.63)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.13)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(1.07)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.83)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.69)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
qstrategy
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.75<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.51<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.75<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.25
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.39<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.41<sup>**</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.28)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.30)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.19)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.15)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
max_einfluss
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.02
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.08
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.13<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.18<sup>*</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
0.00
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.12)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.15)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.10)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.08)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.07)
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
n_women
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.77<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.26
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.61<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.32<sup>**</sup>
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-0.27<sup>**</sup>
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
 
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.22)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.17)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.10)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.11)
</td>
<td style="padding-left: 5px;padding-right: 5px;">
(0.09)
</td>
</tr>
<tr style="border-top: 1px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
AIC
</td>
<td style="padding-left: 5px;padding-right: 5px;">
188.72
</td>
<td style="padding-left: 5px;padding-right: 5px;">
153.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
253.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
337.47
</td>
<td style="padding-left: 5px;padding-right: 5px;">
294.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
419.15
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
BIC
</td>
<td style="padding-left: 5px;padding-right: 5px;">
224.47
</td>
<td style="padding-left: 5px;padding-right: 5px;">
189.07
</td>
<td style="padding-left: 5px;padding-right: 5px;">
289.33
</td>
<td style="padding-left: 5px;padding-right: 5px;">
375.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
331.77
</td>
<td style="padding-left: 5px;padding-right: 5px;">
456.80
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Log Likelihood
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-84.36
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-66.65
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-116.78
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-158.74
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-137.06
</td>
<td style="padding-left: 5px;padding-right: 5px;">
-199.58
</td>
</tr>
<tr>
<td style="padding-left: 5px;padding-right: 5px;">
Deviance
</td>
<td style="padding-left: 5px;padding-right: 5px;">
168.72
</td>
<td style="padding-left: 5px;padding-right: 5px;">
133.31
</td>
<td style="padding-left: 5px;padding-right: 5px;">
233.57
</td>
<td style="padding-left: 5px;padding-right: 5px;">
317.47
</td>
<td style="padding-left: 5px;padding-right: 5px;">
274.12
</td>
<td style="padding-left: 5px;padding-right: 5px;">
399.15
</td>
</tr>
<tr style="border-bottom: 2px solid #000000;">
<td style="padding-left: 5px;padding-right: 5px;">
Num. obs.
</td>
<td style="padding-left: 5px;padding-right: 5px;">
264
</td>
<td style="padding-left: 5px;padding-right: 5px;">
264
</td>
<td style="padding-left: 5px;padding-right: 5px;">
264
</td>
<td style="padding-left: 5px;padding-right: 5px;">
319
</td>
<td style="padding-left: 5px;padding-right: 5px;">
319
</td>
<td style="padding-left: 5px;padding-right: 5px;">
319
</td>
</tr>
</tbody>
<tfoot>
<tr>
<td style="font-size: 0.8em;" colspan="7">
<sup>**</sup>p &lt; 0.05; <sup>*</sup>p &lt; 0.1
</td>
</tr>
</tfoot>
</table>
</section>
<section id="appendix-c" class="level2" data-number="9">
<h2 data-number="9" class="anchored" data-anchor-id="appendix-c"><span class="header-section-number">9</span> Appendix C</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb109"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb109-1"><a href="#cb109-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb109-2"><a href="#cb109-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(rvest)</span>
<span id="cb109-3"><a href="#cb109-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb109-4"><a href="#cb109-4" aria-hidden="true" tabindex="-1"></a>url <span class="ot">&lt;-</span> <span class="st">&quot;https://www.parlament.gv.at/recherchieren/statistiken/personen-statistiken/entw_frauen/NR&quot;</span></span>
<span id="cb109-5"><a href="#cb109-5" aria-hidden="true" tabindex="-1"></a>content <span class="ot">&lt;-</span> <span class="fu">read_html</span>(url)</span>
<span id="cb109-6"><a href="#cb109-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb109-7"><a href="#cb109-7" aria-hidden="true" tabindex="-1"></a>content <span class="sc">%&gt;%</span></span>
<span id="cb109-8"><a href="#cb109-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">html_table</span>() <span class="sc">%&gt;%</span></span>
<span id="cb109-9"><a href="#cb109-9" aria-hidden="true" tabindex="-1"></a>  .[[<span class="dv">1</span>]] <span class="sc">%&gt;%</span></span>
<span id="cb109-10"><a href="#cb109-10" aria-hidden="true" tabindex="-1"></a>  .[<span class="sc">-</span><span class="fu">c</span>(<span class="dv">1</span><span class="sc">:</span><span class="dv">2</span>),] <span class="sc">%&gt;%</span></span>
<span id="cb109-11"><a href="#cb109-11" aria-hidden="true" tabindex="-1"></a>  dplyr<span class="sc">::</span><span class="fu">select</span>(<span class="at">start =</span> Beginn, <span class="st">&quot;percent&quot;</span> <span class="ot">=</span> <span class="st">&quot;%&quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb109-12"><a href="#cb109-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">period =</span> <span class="dv">1</span><span class="sc">:</span><span class="fu">n</span>(),</span>
<span id="cb109-13"><a href="#cb109-13" aria-hidden="true" tabindex="-1"></a>         <span class="at">percent =</span> <span class="fu">gsub</span>(<span class="st">&quot;%&quot;</span>,<span class="st">&quot;&quot;</span>,percent) <span class="sc">%&gt;%</span> </span>
<span id="cb109-14"><a href="#cb109-14" aria-hidden="true" tabindex="-1"></a>           str_trim <span class="sc">%&gt;%</span></span>
<span id="cb109-15"><a href="#cb109-15" aria-hidden="true" tabindex="-1"></a>           <span class="fu">gsub</span>(<span class="st">&quot;,&quot;</span>,<span class="st">&quot;.&quot;</span>,.) <span class="sc">%&gt;%</span></span>
<span id="cb109-16"><a href="#cb109-16" aria-hidden="true" tabindex="-1"></a>           as.numeric) <span class="ot">-&gt;</span> xyxy</span>
<span id="cb109-17"><a href="#cb109-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb109-18"><a href="#cb109-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(xyxy,</span>
<span id="cb109-19"><a href="#cb109-19" aria-hidden="true" tabindex="-1"></a>         <span class="fu">aes</span>(<span class="at">x =</span> period,</span>
<span id="cb109-20"><a href="#cb109-20" aria-hidden="true" tabindex="-1"></a>             <span class="at">y =</span> percent)) <span class="sc">+</span></span>
<span id="cb109-21"><a href="#cb109-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb109-22"><a href="#cb109-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_line</span>() <span class="sc">+</span></span>
<span id="cb109-23"><a href="#cb109-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb109-24"><a href="#cb109-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> xyxy<span class="sc">$</span>period, </span>
<span id="cb109-25"><a href="#cb109-25" aria-hidden="true" tabindex="-1"></a>                     <span class="at">label =</span> <span class="fu">gsub</span>(<span class="st">&quot;Beginn&quot;</span>, <span class="st">&quot;&quot;</span>, xyxy<span class="sc">$</span>start)) <span class="sc">+</span></span>
<span id="cb109-26"><a href="#cb109-26" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;% Women in Nationalrat&quot;</span>) <span class="sc">+</span></span>
<span id="cb109-27"><a href="#cb109-27" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Start of Legislative Period</span><span class="sc">\n</span><span class="st">(DD.MM.YYYY)&quot;</span>) <span class="sc">+</span></span>
<span id="cb109-28"><a href="#cb109-28" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">axis.text.x =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">90</span>, <span class="at">vjust =</span> <span class="fl">0.5</span>, <span class="at">hjust=</span><span class="dv">1</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="data:image/png;base64,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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="appendix-d" class="level2" data-number="10">
<h2 data-number="10" class="anchored" data-anchor-id="appendix-d"><span class="header-section-number">10</span> Appendix D</h2>
<p>Was created manually.</p>
</section>
<section id="appendix-e" class="level2" data-number="11">
<h2 data-number="11" class="anchored" data-anchor-id="appendix-e"><span class="header-section-number">11</span> Appendix E</h2>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb110"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb110-1"><a href="#cb110-1" aria-hidden="true" tabindex="-1"></a><span class="do">#####################################################</span></span>
<span id="cb110-2"><a href="#cb110-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Descriptive (Appendix E)</span></span>
<span id="cb110-3"><a href="#cb110-3" aria-hidden="true" tabindex="-1"></a><span class="do">#####################################################</span></span>
<span id="cb110-4"><a href="#cb110-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb110-5"><a href="#cb110-5" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span> </span>
<span id="cb110-6"><a href="#cb110-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(max_einfluss) <span class="sc">%&gt;%</span></span>
<span id="cb110-7"><a href="#cb110-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb110-8"><a href="#cb110-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">n =</span> n<span class="sc">/</span><span class="dv">9</span>) <span class="sc">%&gt;%</span></span>
<span id="cb110-9"><a href="#cb110-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb110-10"><a href="#cb110-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%&gt;%</span></span>
<span id="cb110-11"><a href="#cb110-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> max_einfluss, <span class="at">y =</span> percent,</span>
<span id="cb110-12"><a href="#cb110-12" aria-hidden="true" tabindex="-1"></a>             <span class="at">fill =</span> <span class="fu">factor</span>(max_einfluss))) <span class="sc">+</span></span>
<span id="cb110-13"><a href="#cb110-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_col</span>() <span class="sc">+</span></span>
<span id="cb110-14"><a href="#cb110-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb110-15"><a href="#cb110-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;%&quot;</span>) <span class="sc">+</span></span>
<span id="cb110-16"><a href="#cb110-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span></span>
<span id="cb110-17"><a href="#cb110-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Impact on Candidate Selection&quot;</span>) <span class="sc">+</span></span>
<span id="cb110-18"><a href="#cb110-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">7</span>,</span>
<span id="cb110-19"><a href="#cb110-19" aria-hidden="true" tabindex="-1"></a>                     <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">&quot;min.&quot;</span>,<span class="fu">rep</span>(<span class="st">&quot;...&quot;</span>,<span class="dv">5</span>),<span class="st">&quot;max.&quot;</span>)) <span class="sc">+</span></span>
<span id="cb110-20"><a href="#cb110-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb111"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb111-1"><a href="#cb111-1" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span> </span>
<span id="cb111-2"><a href="#cb111-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">qstrategy =</span> <span class="fu">as.numeric</span>(qstrategy)) <span class="sc">%&gt;%</span></span>
<span id="cb111-3"><a href="#cb111-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(qstrategy) <span class="sc">%&gt;%</span></span>
<span id="cb111-4"><a href="#cb111-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb111-5"><a href="#cb111-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">n =</span> n<span class="sc">/</span><span class="dv">9</span>) <span class="sc">%&gt;%</span></span>
<span id="cb111-6"><a href="#cb111-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb111-7"><a href="#cb111-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%&gt;%</span></span>
<span id="cb111-8"><a href="#cb111-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> qstrategy, <span class="at">y =</span> percent,</span>
<span id="cb111-9"><a href="#cb111-9" aria-hidden="true" tabindex="-1"></a>             <span class="at">fill =</span> <span class="fu">factor</span>(qstrategy))) <span class="sc">+</span></span>
<span id="cb111-10"><a href="#cb111-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_col</span>() <span class="sc">+</span></span>
<span id="cb111-11"><a href="#cb111-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb111-12"><a href="#cb111-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;%&quot;</span>) <span class="sc">+</span></span>
<span id="cb111-13"><a href="#cb111-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;Selection Strategy&quot;</span>) <span class="sc">+</span></span>
<span id="cb111-14"><a href="#cb111-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">5</span>,</span>
<span id="cb111-15"><a href="#cb111-15" aria-hidden="true" tabindex="-1"></a>                     <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">&quot;exclusively</span><span class="sc">\n</span><span class="st">individual</span><span class="sc">\n</span><span class="st">characteristics&quot;</span>,</span>
<span id="cb111-16"><a href="#cb111-16" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;...&quot;</span>,</span>
<span id="cb111-17"><a href="#cb111-17" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;both</span><span class="sc">\n</span><span class="st">equally&quot;</span>,</span>
<span id="cb111-18"><a href="#cb111-18" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;...&quot;</span>,</span>
<span id="cb111-19"><a href="#cb111-19" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;exclusively</span><span class="sc">\n</span><span class="st">list</span><span class="sc">\n</span><span class="st">composition&quot;</span>)) <span class="sc">+</span></span>
<span id="cb111-20"><a href="#cb111-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb111-21"><a href="#cb111-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">5</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" class="img-fluid" width="672"></p>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb112"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb112-1"><a href="#cb112-1" aria-hidden="true" tabindex="-1"></a>df <span class="sc">%&gt;%</span> </span>
<span id="cb112-2"><a href="#cb112-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">qstrategy =</span> <span class="fu">as.numeric</span>(n_women)) <span class="sc">%&gt;%</span></span>
<span id="cb112-3"><a href="#cb112-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(n_women) <span class="sc">%&gt;%</span></span>
<span id="cb112-4"><a href="#cb112-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>() <span class="sc">%&gt;%</span></span>
<span id="cb112-5"><a href="#cb112-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">n =</span> n<span class="sc">/</span><span class="dv">9</span>) <span class="sc">%&gt;%</span></span>
<span id="cb112-6"><a href="#cb112-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb112-7"><a href="#cb112-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%&gt;%</span></span>
<span id="cb112-8"><a href="#cb112-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> n_women, <span class="at">y =</span> percent,</span>
<span id="cb112-9"><a href="#cb112-9" aria-hidden="true" tabindex="-1"></a>             <span class="at">fill =</span> <span class="fu">factor</span>(n_women))) <span class="sc">+</span></span>
<span id="cb112-10"><a href="#cb112-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_col</span>() <span class="sc">+</span></span>
<span id="cb112-11"><a href="#cb112-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb112-12"><a href="#cb112-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;%&quot;</span>) <span class="sc">+</span></span>
<span id="cb112-13"><a href="#cb112-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="st">&quot;# Women Stage 1&quot;</span>) <span class="sc">+</span></span>
<span id="cb112-14"><a href="#cb112-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">8</span>) <span class="sc">+</span></span>
<span id="cb112-15"><a href="#cb112-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">fill =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb112-16"><a href="#cb112-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">8</span>)) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<p><img 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" class="img-fluid" width="672"></p>
</section>
<section id="appendix-k" class="level2" data-number="12">
<h2 data-number="12" class="anchored" data-anchor-id="appendix-k"><span class="header-section-number">12</span> Appendix K</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb113"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb113-1"><a href="#cb113-1" aria-hidden="true" tabindex="-1"></a><span class="do">####################################################</span></span>
<span id="cb113-2"><a href="#cb113-2" aria-hidden="true" tabindex="-1"></a><span class="co"># AMCE Plot for All CJ Attributes (APPENDIX K)</span></span>
<span id="cb113-3"><a href="#cb113-3" aria-hidden="true" tabindex="-1"></a><span class="do">####################################################</span></span>
<span id="cb113-4"><a href="#cb113-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb113-5"><a href="#cb113-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Baseline Model</span></span>
<span id="cb113-6"><a href="#cb113-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb113-7"><a href="#cb113-7" aria-hidden="true" tabindex="-1"></a>f0 <span class="ot">&lt;-</span> <span class="fu">names</span>(df)[<span class="fu">grepl</span>(<span class="st">&quot;fct_.*?_[A-Za-z]+&quot;</span>, <span class="fu">names</span>(df))]</span>
<span id="cb113-8"><a href="#cb113-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb113-9"><a href="#cb113-9" aria-hidden="true" tabindex="-1"></a>get_amce_mlogit <span class="ot">&lt;-</span> <span class="cf">function</span>(<span class="at">var =</span> <span class="st">&quot;fct_gender_Male&quot;</span>){</span>
<span id="cb113-10"><a href="#cb113-10" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-11"><a href="#cb113-11" aria-hidden="true" tabindex="-1"></a>  pred0 <span class="ot">&lt;-</span> <span class="fu">mnl_fd_ova</span>(<span class="at">model =</span> mod0,</span>
<span id="cb113-12"><a href="#cb113-12" aria-hidden="true" tabindex="-1"></a>                    <span class="at">data =</span> df,</span>
<span id="cb113-13"><a href="#cb113-13" aria-hidden="true" tabindex="-1"></a>                    <span class="at">x =</span> var,</span>
<span id="cb113-14"><a href="#cb113-14" aria-hidden="true" tabindex="-1"></a>                    <span class="at">by =</span> <span class="dv">1</span>,</span>
<span id="cb113-15"><a href="#cb113-15" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z =</span> var,</span>
<span id="cb113-16"><a href="#cb113-16" aria-hidden="true" tabindex="-1"></a>                    <span class="at">z_values =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">1</span>),</span>
<span id="cb113-17"><a href="#cb113-17" aria-hidden="true" tabindex="-1"></a>                    <span class="at">seed =</span> <span class="dv">123123</span>,</span>
<span id="cb113-18"><a href="#cb113-18" aria-hidden="true" tabindex="-1"></a>                    <span class="at">nsim =</span> <span class="dv">100</span>, <span class="co"># faster</span></span>
<span id="cb113-19"><a href="#cb113-19" aria-hidden="true" tabindex="-1"></a>                    <span class="at">probs =</span> <span class="fu">c</span>(<span class="fl">0.025</span>, <span class="fl">0.975</span>))</span>
<span id="cb113-20"><a href="#cb113-20" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-21"><a href="#cb113-21" aria-hidden="true" tabindex="-1"></a>  pd0 <span class="ot">&lt;-</span> pred0<span class="sc">$</span>plotdata_fd <span class="sc">%&gt;%</span> </span>
<span id="cb113-22"><a href="#cb113-22" aria-hidden="true" tabindex="-1"></a>    dplyr<span class="sc">::</span><span class="fu">filter</span>(<span class="fu">get</span>(var) <span class="sc">==</span> <span class="dv">1</span>)</span>
<span id="cb113-23"><a href="#cb113-23" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-24"><a href="#cb113-24" aria-hidden="true" tabindex="-1"></a>  pd0<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">is.na</span>(<span class="fu">as.numeric</span>(pd0<span class="sc">$</span>ballotposition_new)),</span>
<span id="cb113-25"><a href="#cb113-25" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;Deselected&quot;</span>,</span>
<span id="cb113-26"><a href="#cb113-26" aria-hidden="true" tabindex="-1"></a>                                 <span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>, pd0<span class="sc">$</span>ballotposition_new))</span>
<span id="cb113-27"><a href="#cb113-27" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-28"><a href="#cb113-28" aria-hidden="true" tabindex="-1"></a>  pd0<span class="sc">$</span>ballotposition_new <span class="ot">&lt;-</span> <span class="fu">factor</span>(pd0<span class="sc">$</span>ballotposition_new,</span>
<span id="cb113-29"><a href="#cb113-29" aria-hidden="true" tabindex="-1"></a>                                 <span class="at">levels =</span> <span class="fu">c</span>(<span class="fu">paste0</span>(<span class="st">&quot;Position: &quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>), <span class="st">&quot;Deselected&quot;</span>))</span>
<span id="cb113-30"><a href="#cb113-30" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-31"><a href="#cb113-31" aria-hidden="true" tabindex="-1"></a>  pd0[[var]] <span class="ot">&lt;-</span> <span class="cn">NULL</span></span>
<span id="cb113-32"><a href="#cb113-32" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-33"><a href="#cb113-33" aria-hidden="true" tabindex="-1"></a>  pd0<span class="sc">$</span>fct <span class="ot">&lt;-</span> var</span>
<span id="cb113-34"><a href="#cb113-34" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb113-35"><a href="#cb113-35" aria-hidden="true" tabindex="-1"></a>  pd0</span>
<span id="cb113-36"><a href="#cb113-36" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb113-37"><a href="#cb113-37" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb113-38"><a href="#cb113-38" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb113-39"><a href="#cb113-39" aria-hidden="true" tabindex="-1"></a>all_fct <span class="ot">&lt;-</span> <span class="fu">map_df</span>(f0, get_amce_mlogit)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>First scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!

Second scenario:
Multiplying values with simulated estimates:
================================================================================
Applying link function:
================================================================================
Done!</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in ifelse(is.na(as.numeric(pd0$ballotposition_new)), &quot;Deselected&quot;, :
NAs durch Umwandlung erzeugt</code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb148"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb148-1"><a href="#cb148-1" aria-hidden="true" tabindex="-1"></a>all_fct<span class="sc">$</span>attribute <span class="ot">&lt;-</span> <span class="fu">str_extract</span>(all_fct<span class="sc">$</span>fct,</span>
<span id="cb148-2"><a href="#cb148-2" aria-hidden="true" tabindex="-1"></a>                                 <span class="st">&quot;^fct_.*?_&quot;</span>) <span class="sc">%&gt;%</span></span>
<span id="cb148-3"><a href="#cb148-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">gsub</span>(<span class="st">&quot;fct_|_$&quot;</span>, <span class="st">&quot;&quot;</span>, .)</span>
<span id="cb148-4"><a href="#cb148-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb148-5"><a href="#cb148-5" aria-hidden="true" tabindex="-1"></a>all_fct<span class="sc">$</span>level <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;^fct_(.*?)_&quot;</span>, <span class="st">&quot;&quot;</span>, all_fct<span class="sc">$</span>fct)</span>
<span id="cb148-6"><a href="#cb148-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb148-7"><a href="#cb148-7" aria-hidden="true" tabindex="-1"></a>color_fill <span class="ot">&lt;-</span> <span class="fu">colorRampPalette</span>(<span class="fu">c</span>(<span class="st">&quot;#010b8c&quot;</span>, <span class="st">&quot;#b882fa&quot;</span>))</span>
<span id="cb148-8"><a href="#cb148-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb148-9"><a href="#cb148-9" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> all_fct, <span class="fu">aes</span>(<span class="at">x =</span> ballotposition_new, </span>
<span id="cb148-10"><a href="#cb148-10" aria-hidden="true" tabindex="-1"></a>                       <span class="at">y =</span> mean,</span>
<span id="cb148-11"><a href="#cb148-11" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymin =</span> lower, </span>
<span id="cb148-12"><a href="#cb148-12" aria-hidden="true" tabindex="-1"></a>                       <span class="at">ymax =</span> upper,</span>
<span id="cb148-13"><a href="#cb148-13" aria-hidden="true" tabindex="-1"></a>                       <span class="at">color =</span> ballotposition_new)) <span class="sc">+</span></span>
<span id="cb148-14"><a href="#cb148-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">lty=</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb148-15"><a href="#cb148-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fu">seq</span>(<span class="sc">-</span><span class="fl">0.2</span>,<span class="fl">0.20</span>,<span class="at">by=</span><span class="fl">0.05</span>), </span>
<span id="cb148-16"><a href="#cb148-16" aria-hidden="true" tabindex="-1"></a>             <span class="at">lty=</span> <span class="dv">3</span>,</span>
<span id="cb148-17"><a href="#cb148-17" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> <span class="st">&quot;grey85&quot;</span>) <span class="sc">+</span></span>
<span id="cb148-18"><a href="#cb148-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_pointrange</span>() <span class="sc">+</span></span>
<span id="cb148-19"><a href="#cb148-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb148-20"><a href="#cb148-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">xlab</span>(<span class="cn">NULL</span>) <span class="sc">+</span></span>
<span id="cb148-21"><a href="#cb148-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ylab</span>(<span class="st">&quot;Effect&quot;</span>) <span class="sc">+</span></span>
<span id="cb148-22"><a href="#cb148-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb148-23"><a href="#cb148-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">color_fill</span>(<span class="dv">7</span>)) <span class="sc">+</span></span>
<span id="cb148-24"><a href="#cb148-24" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb148-25"><a href="#cb148-25" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">panel.grid.minor =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb148-26"><a href="#cb148-26" aria-hidden="true" tabindex="-1"></a>        <span class="at">panel.grid.major =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span></span>
<span id="cb148-27"><a href="#cb148-27" aria-hidden="true" tabindex="-1"></a>  ggh4x<span class="sc">::</span><span class="fu">facet_nested</span>(attribute <span class="sc">+</span> level <span class="sc">~</span> ., </span>
<span id="cb148-28"><a href="#cb148-28" aria-hidden="true" tabindex="-1"></a>                      <span class="at">scales  =</span><span class="st">&quot;free&quot;</span>, </span>
<span id="cb148-29"><a href="#cb148-29" aria-hidden="true" tabindex="-1"></a>                      <span class="at">space =</span> <span class="st">&quot;free&quot;</span>,</span>
<span id="cb148-30"><a href="#cb148-30" aria-hidden="true" tabindex="-1"></a>                      <span class="at">switch =</span> <span class="st">&quot;y&quot;</span>)   <span class="sc">+</span></span>
<span id="cb148-31"><a href="#cb148-31" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_discrete</span>(<span class="at">position=</span><span class="st">&quot;top&quot;</span>) <span class="sc">+</span></span>
<span id="cb148-32"><a href="#cb148-32" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme</span>(<span class="at">plot.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&#39;white&#39;</span>),</span>
<span id="cb148-33"><a href="#cb148-33" aria-hidden="true" tabindex="-1"></a>        <span class="at">axis.text.y =</span> <span class="fu">element_text</span>(<span class="at">size=</span><span class="fl">10.5</span>),</span>
<span id="cb148-34"><a href="#cb148-34" aria-hidden="true" tabindex="-1"></a>        <span class="at">axis.text.x =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>,</span>
<span id="cb148-35"><a href="#cb148-35" aria-hidden="true" tabindex="-1"></a>                                   <span class="at">size=</span><span class="fl">10.5</span>),</span>
<span id="cb148-36"><a href="#cb148-36" aria-hidden="true" tabindex="-1"></a>        <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">90</span>,</span>
<span id="cb148-37"><a href="#cb148-37" aria-hidden="true" tabindex="-1"></a>                                    <span class="at">size =</span> <span class="fl">10.5</span>),</span>
<span id="cb148-38"><a href="#cb148-38" aria-hidden="true" tabindex="-1"></a>        <span class="at">strip.text.y.left =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb148-39"><a href="#cb148-39" aria-hidden="true" tabindex="-1"></a>        <span class="at">strip.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&#39;white&#39;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="appendix-k-1" class="level2" data-number="13">
<h2 data-number="13" class="anchored" data-anchor-id="appendix-k-1"><span class="header-section-number">13</span> Appendix K</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb149"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb149-1"><a href="#cb149-1" aria-hidden="true" tabindex="-1"></a>flist <span class="ot">=</span> <span class="fu">list</span>(<span class="st">&quot;fct_gender&quot;</span> <span class="ot">=</span> <span class="st">&quot;Gender&quot;</span>,</span>
<span id="cb149-2"><a href="#cb149-2" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_age&quot;</span> <span class="ot">=</span> <span class="st">&quot;Age&quot;</span>,</span>
<span id="cb149-3"><a href="#cb149-3" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_issue&quot;</span> <span class="ot">=</span> <span class="st">&quot;Policy</span><span class="sc">\n</span><span class="st">Expertise&quot;</span>,</span>
<span id="cb149-4"><a href="#cb149-4" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_deviation&quot;</span> <span class="ot">=</span> <span class="st">&quot;Deviation from</span><span class="sc">\n</span><span class="st">party&quot;</span>,</span>
<span id="cb149-5"><a href="#cb149-5" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_experience&quot;</span> <span class="ot">=</span> <span class="st">&quot;Incumbency&quot;</span>,</span>
<span id="cb149-6"><a href="#cb149-6" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_personalvotes&quot;</span> <span class="ot">=</span> <span class="st">&quot;Personal</span><span class="sc">\n</span><span class="st">Votes&quot;</span>,</span>
<span id="cb149-7"><a href="#cb149-7" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_otherlist&quot;</span> <span class="ot">=</span> <span class="st">&quot;Dual</span><span class="sc">\n</span><span class="st">Candidacy&quot;</span>,</span>
<span id="cb149-8"><a href="#cb149-8" aria-hidden="true" tabindex="-1"></a>             <span class="st">&quot;fct_position&quot;</span> <span class="ot">=</span> <span class="st">&quot;Intra-Party</span><span class="sc">\n</span><span class="st">Position&quot;</span>)</span>
<span id="cb149-9"><a href="#cb149-9" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-10"><a href="#cb149-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-11"><a href="#cb149-11" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos1 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">1</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-12"><a href="#cb149-12" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos1[<span class="fu">is.na</span>(df<span class="sc">$</span>pos1)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-13"><a href="#cb149-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-14"><a href="#cb149-14" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos2 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">2</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-15"><a href="#cb149-15" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos2[<span class="fu">is.na</span>(df<span class="sc">$</span>pos2)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-16"><a href="#cb149-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-17"><a href="#cb149-17" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos3 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">3</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-18"><a href="#cb149-18" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos3[<span class="fu">is.na</span>(df<span class="sc">$</span>pos3)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-19"><a href="#cb149-19" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-20"><a href="#cb149-20" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos4 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">4</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-21"><a href="#cb149-21" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos4[<span class="fu">is.na</span>(df<span class="sc">$</span>pos4)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-22"><a href="#cb149-22" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-23"><a href="#cb149-23" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos5 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">5</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-24"><a href="#cb149-24" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos5[<span class="fu">is.na</span>(df<span class="sc">$</span>pos5)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-25"><a href="#cb149-25" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-26"><a href="#cb149-26" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos6 <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(<span class="fu">as.numeric</span>(df<span class="sc">$</span>ballotposition) <span class="sc">==</span> <span class="dv">6</span>, <span class="dv">1</span>, <span class="dv">0</span>)</span>
<span id="cb149-27"><a href="#cb149-27" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>pos6[<span class="fu">is.na</span>(df<span class="sc">$</span>pos6)] <span class="ot">&lt;-</span> <span class="dv">0</span></span>
<span id="cb149-28"><a href="#cb149-28" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-29"><a href="#cb149-29" aria-hidden="true" tabindex="-1"></a>df<span class="sc">$</span>region <span class="ot">&lt;-</span> <span class="fu">case_when</span>(df<span class="sc">$</span>ebene1 <span class="sc">==</span> <span class="dv">1</span> <span class="sc">~</span> <span class="dv">1</span>,</span>
<span id="cb149-30"><a href="#cb149-30" aria-hidden="true" tabindex="-1"></a>                       df<span class="sc">$</span>ebene2 <span class="sc">==</span> <span class="dv">1</span> <span class="sc">~</span> <span class="dv">2</span>,</span>
<span id="cb149-31"><a href="#cb149-31" aria-hidden="true" tabindex="-1"></a>                       df<span class="sc">$</span>ebene3 <span class="sc">==</span> <span class="dv">1</span> <span class="sc">~</span> <span class="dv">3</span>,</span>
<span id="cb149-32"><a href="#cb149-32" aria-hidden="true" tabindex="-1"></a>                       df<span class="sc">$</span>ebene4 <span class="sc">==</span> <span class="dv">1</span> <span class="sc">~</span> <span class="dv">0</span>)</span>
<span id="cb149-33"><a href="#cb149-33" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb149-34"><a href="#cb149-34" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb149-35"><a href="#cb149-35" aria-hidden="true" tabindex="-1"></a><span class="co"># Descriptive Table (part of table 1)</span></span>
<span id="cb149-36"><a href="#cb149-36" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb149-37"><a href="#cb149-37" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb149-38"><a href="#cb149-38" aria-hidden="true" tabindex="-1"></a>respondents <span class="sc">%&gt;%</span> </span>
<span id="cb149-39"><a href="#cb149-39" aria-hidden="true" tabindex="-1"></a>  <span class="fu">group_by</span>(party) <span class="sc">%&gt;%</span> </span>
<span id="cb149-40"><a href="#cb149-40" aria-hidden="true" tabindex="-1"></a>  count <span class="sc">%&gt;%</span></span>
<span id="cb149-41"><a href="#cb149-41" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ungroup</span>() <span class="sc">%&gt;%</span></span>
<span id="cb149-42"><a href="#cb149-42" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">percent =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 5 × 3
  party      n percent
  &lt;chr&gt;  &lt;int&gt;   &lt;dbl&gt;
1 FPO       19    5.86
2 Gruene   121   37.3 
3 NEOS      40   12.3 
4 OVP       56   17.3 
5 SPO       88   27.2 </code></pre>
</div>
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb151"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb151-1"><a href="#cb151-1" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb151-2"><a href="#cb151-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Basic AMCE/MM Plots (Appendix K)</span></span>
<span id="cb151-3"><a href="#cb151-3" aria-hidden="true" tabindex="-1"></a><span class="do">####################################</span></span>
<span id="cb151-4"><a href="#cb151-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb151-5"><a href="#cb151-5" aria-hidden="true" tabindex="-1"></a>plot_amce_mm <span class="ot">&lt;-</span> <span class="cf">function</span>(<span class="at">dv =</span> <span class="st">&quot;&quot;</span>){</span>
<span id="cb151-6"><a href="#cb151-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb151-7"><a href="#cb151-7" aria-hidden="true" tabindex="-1"></a>  df<span class="sc">$</span>depvar <span class="ot">&lt;-</span> df[[dv]]</span>
<span id="cb151-8"><a href="#cb151-8" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-9"><a href="#cb151-9" aria-hidden="true" tabindex="-1"></a>  mm_base <span class="ot">&lt;-</span> cregg<span class="sc">::</span><span class="fu">cj</span>(depvar <span class="sc">~</span> </span>
<span id="cb151-10"><a href="#cb151-10" aria-hidden="true" tabindex="-1"></a>                         fct_gender <span class="sc">+</span></span>
<span id="cb151-11"><a href="#cb151-11" aria-hidden="true" tabindex="-1"></a>                         fct_age <span class="sc">+</span></span>
<span id="cb151-12"><a href="#cb151-12" aria-hidden="true" tabindex="-1"></a>                         fct_issue <span class="sc">+</span> </span>
<span id="cb151-13"><a href="#cb151-13" aria-hidden="true" tabindex="-1"></a>                         fct_deviation <span class="sc">+</span> fct_personalvotes <span class="sc">+</span></span>
<span id="cb151-14"><a href="#cb151-14" aria-hidden="true" tabindex="-1"></a>                         fct_experience <span class="sc">+</span></span>
<span id="cb151-15"><a href="#cb151-15" aria-hidden="true" tabindex="-1"></a>                         fct_position <span class="sc">+</span></span>
<span id="cb151-16"><a href="#cb151-16" aria-hidden="true" tabindex="-1"></a>                         fct_otherlist,</span>
<span id="cb151-17"><a href="#cb151-17" aria-hidden="true" tabindex="-1"></a>                       <span class="at">data =</span> df,</span>
<span id="cb151-18"><a href="#cb151-18" aria-hidden="true" tabindex="-1"></a>                       <span class="at">id =</span> <span class="sc">~</span> id,</span>
<span id="cb151-19"><a href="#cb151-19" aria-hidden="true" tabindex="-1"></a>                       <span class="at">estimate =</span> <span class="st">&quot;mm&quot;</span>,</span>
<span id="cb151-20"><a href="#cb151-20" aria-hidden="true" tabindex="-1"></a>                       <span class="at">feature_labels =</span> flist)</span>
<span id="cb151-21"><a href="#cb151-21" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-22"><a href="#cb151-22" aria-hidden="true" tabindex="-1"></a>  amce_base <span class="ot">&lt;-</span> cregg<span class="sc">::</span><span class="fu">cj</span>(depvar <span class="sc">~</span> </span>
<span id="cb151-23"><a href="#cb151-23" aria-hidden="true" tabindex="-1"></a>                           fct_gender <span class="sc">+</span></span>
<span id="cb151-24"><a href="#cb151-24" aria-hidden="true" tabindex="-1"></a>                           fct_age <span class="sc">+</span></span>
<span id="cb151-25"><a href="#cb151-25" aria-hidden="true" tabindex="-1"></a>                           fct_issue <span class="sc">+</span> </span>
<span id="cb151-26"><a href="#cb151-26" aria-hidden="true" tabindex="-1"></a>                           fct_deviation <span class="sc">+</span> fct_personalvotes <span class="sc">+</span></span>
<span id="cb151-27"><a href="#cb151-27" aria-hidden="true" tabindex="-1"></a>                           fct_experience <span class="sc">+</span></span>
<span id="cb151-28"><a href="#cb151-28" aria-hidden="true" tabindex="-1"></a>                           fct_position <span class="sc">+</span></span>
<span id="cb151-29"><a href="#cb151-29" aria-hidden="true" tabindex="-1"></a>                           fct_otherlist,</span>
<span id="cb151-30"><a href="#cb151-30" aria-hidden="true" tabindex="-1"></a>                         <span class="at">data =</span> df,</span>
<span id="cb151-31"><a href="#cb151-31" aria-hidden="true" tabindex="-1"></a>                         <span class="at">id =</span> <span class="sc">~</span> id,</span>
<span id="cb151-32"><a href="#cb151-32" aria-hidden="true" tabindex="-1"></a>                         <span class="at">estimate =</span> <span class="st">&quot;amce&quot;</span>,</span>
<span id="cb151-33"><a href="#cb151-33" aria-hidden="true" tabindex="-1"></a>                         <span class="at">feature_labels =</span> flist)</span>
<span id="cb151-34"><a href="#cb151-34" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-35"><a href="#cb151-35" aria-hidden="true" tabindex="-1"></a>  mm_base <span class="ot">&lt;-</span> <span class="fu">bind_rows</span>(mm_base, amce_base)</span>
<span id="cb151-36"><a href="#cb151-36" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-37"><a href="#cb151-37" aria-hidden="true" tabindex="-1"></a>  <span class="cf">if</span>(<span class="fu">grepl</span>(<span class="st">&quot;pos&quot;</span>, dv)){</span>
<span id="cb151-38"><a href="#cb151-38" aria-hidden="true" tabindex="-1"></a>    </span>
<span id="cb151-39"><a href="#cb151-39" aria-hidden="true" tabindex="-1"></a>    mmline <span class="ot">&lt;-</span> <span class="dv">1</span><span class="sc">/</span><span class="dv">9</span></span>
<span id="cb151-40"><a href="#cb151-40" aria-hidden="true" tabindex="-1"></a>    </span>
<span id="cb151-41"><a href="#cb151-41" aria-hidden="true" tabindex="-1"></a>  } <span class="cf">else</span>{</span>
<span id="cb151-42"><a href="#cb151-42" aria-hidden="true" tabindex="-1"></a>    </span>
<span id="cb151-43"><a href="#cb151-43" aria-hidden="true" tabindex="-1"></a>    mmline <span class="ot">&lt;-</span> <span class="dv">1</span><span class="sc">/</span><span class="dv">3</span></span>
<span id="cb151-44"><a href="#cb151-44" aria-hidden="true" tabindex="-1"></a>    </span>
<span id="cb151-45"><a href="#cb151-45" aria-hidden="true" tabindex="-1"></a>  }</span>
<span id="cb151-46"><a href="#cb151-46" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-47"><a href="#cb151-47" aria-hidden="true" tabindex="-1"></a>  hline_data <span class="ot">&lt;-</span> <span class="fu">data.frame</span>(<span class="st">&quot;statistic&quot;</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">&quot;AMCE&quot;</span>, <span class="st">&quot;MM&quot;</span>),</span>
<span id="cb151-48"><a href="#cb151-48" aria-hidden="true" tabindex="-1"></a>                           <span class="at">value =</span> <span class="fu">c</span>(<span class="dv">0</span>,mmline))</span>
<span id="cb151-49"><a href="#cb151-49" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-50"><a href="#cb151-50" aria-hidden="true" tabindex="-1"></a>  mm_base<span class="sc">$</span>statistic <span class="ot">&lt;-</span> <span class="fu">ifelse</span>(mm_base<span class="sc">$</span>statistic <span class="sc">==</span> <span class="st">&quot;mm&quot;</span>,</span>
<span id="cb151-51"><a href="#cb151-51" aria-hidden="true" tabindex="-1"></a>                              <span class="st">&quot;MM&quot;</span>, <span class="st">&quot;AMCE&quot;</span>)</span>
<span id="cb151-52"><a href="#cb151-52" aria-hidden="true" tabindex="-1"></a>  </span>
<span id="cb151-53"><a href="#cb151-53" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(mm_base, </span>
<span id="cb151-54"><a href="#cb151-54" aria-hidden="true" tabindex="-1"></a>         <span class="fu">aes</span>(<span class="at">x =</span> level, </span>
<span id="cb151-55"><a href="#cb151-55" aria-hidden="true" tabindex="-1"></a>             <span class="at">y =</span> estimate,</span>
<span id="cb151-56"><a href="#cb151-56" aria-hidden="true" tabindex="-1"></a>             <span class="at">color =</span> feature)) <span class="sc">+</span></span>
<span id="cb151-57"><a href="#cb151-57" aria-hidden="true" tabindex="-1"></a>    <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb151-58"><a href="#cb151-58" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_hline</span>(<span class="at">data =</span> hline_data, <span class="fu">aes</span>(<span class="at">yintercept =</span> value), <span class="at">lty =</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb151-59"><a href="#cb151-59" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_point</span>(<span class="at">size =</span> <span class="fl">1.5</span>, </span>
<span id="cb151-60"><a href="#cb151-60" aria-hidden="true" tabindex="-1"></a>               <span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> <span class="fl">0.8</span>)) <span class="sc">+</span></span>
<span id="cb151-61"><a href="#cb151-61" aria-hidden="true" tabindex="-1"></a>    <span class="fu">geom_errorbar</span>(<span class="fu">aes</span>(<span class="at">ymax =</span> lower, </span>
<span id="cb151-62"><a href="#cb151-62" aria-hidden="true" tabindex="-1"></a>                      <span class="at">ymin =</span> upper, </span>
<span id="cb151-63"><a href="#cb151-63" aria-hidden="true" tabindex="-1"></a>                      <span class="at">width =</span> <span class="dv">0</span>),</span>
<span id="cb151-64"><a href="#cb151-64" aria-hidden="true" tabindex="-1"></a>                  <span class="at">position =</span> <span class="fu">position_dodge</span>(<span class="at">width =</span> <span class="fl">0.8</span>)) <span class="sc">+</span></span>
<span id="cb151-65"><a href="#cb151-65" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb151-66"><a href="#cb151-66" aria-hidden="true" tabindex="-1"></a>    ggh4x<span class="sc">::</span><span class="fu">facet_nested</span>(feature <span class="sc">~</span> statistic, </span>
<span id="cb151-67"><a href="#cb151-67" aria-hidden="true" tabindex="-1"></a>                        <span class="at">scales  =</span><span class="st">&quot;free&quot;</span>, </span>
<span id="cb151-68"><a href="#cb151-68" aria-hidden="true" tabindex="-1"></a>                        <span class="at">space =</span> <span class="st">&quot;free_y&quot;</span>,</span>
<span id="cb151-69"><a href="#cb151-69" aria-hidden="true" tabindex="-1"></a>                        <span class="at">switch =</span> <span class="st">&quot;y&quot;</span>) <span class="sc">+</span></span>
<span id="cb151-70"><a href="#cb151-70" aria-hidden="true" tabindex="-1"></a>    <span class="fu">scale_x_discrete</span>(<span class="at">position=</span><span class="st">&quot;top&quot;</span>) <span class="sc">+</span></span>
<span id="cb151-71"><a href="#cb151-71" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">plot.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&#39;white&#39;</span>),</span>
<span id="cb151-72"><a href="#cb151-72" aria-hidden="true" tabindex="-1"></a>          <span class="at">axis.text.y =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">9</span>),</span>
<span id="cb151-73"><a href="#cb151-73" aria-hidden="true" tabindex="-1"></a>          <span class="at">axis.text.x =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>,</span>
<span id="cb151-74"><a href="#cb151-74" aria-hidden="true" tabindex="-1"></a>                                     <span class="at">size =</span> <span class="dv">9</span>),</span>
<span id="cb151-75"><a href="#cb151-75" aria-hidden="true" tabindex="-1"></a>          <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">90</span>,</span>
<span id="cb151-76"><a href="#cb151-76" aria-hidden="true" tabindex="-1"></a>                                      <span class="at">size =</span> <span class="dv">9</span>),</span>
<span id="cb151-77"><a href="#cb151-77" aria-hidden="true" tabindex="-1"></a>          <span class="at">strip.text.y.left =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb151-78"><a href="#cb151-78" aria-hidden="true" tabindex="-1"></a>          <span class="at">strip.background =</span> <span class="fu">element_rect</span>(<span class="at">fill =</span> <span class="st">&#39;white&#39;</span>)) <span class="sc">+</span></span>
<span id="cb151-79"><a href="#cb151-79" aria-hidden="true" tabindex="-1"></a>    <span class="fu">theme</span>(<span class="at">plot.margin=</span><span class="fu">unit</span>(<span class="fu">c</span>(<span class="dv">1</span>,<span class="dv">1</span>,<span class="dv">1</span>,<span class="dv">3</span>),</span>
<span id="cb151-80"><a href="#cb151-80" aria-hidden="true" tabindex="-1"></a>                           <span class="st">&quot;line&quot;</span>),</span>
<span id="cb151-81"><a href="#cb151-81" aria-hidden="true" tabindex="-1"></a>          <span class="at">panel.border =</span> <span class="fu">element_rect</span>(<span class="at">colour =</span> <span class="st">&quot;black&quot;</span>),</span>
<span id="cb151-82"><a href="#cb151-82" aria-hidden="true" tabindex="-1"></a>          <span class="at">legend.position =</span> <span class="st">&quot;bottom&quot;</span>) <span class="sc">+</span></span>
<span id="cb151-83"><a href="#cb151-83" aria-hidden="true" tabindex="-1"></a>    <span class="fu">xlab</span>(<span class="cn">NULL</span>) <span class="sc">+</span></span>
<span id="cb151-84"><a href="#cb151-84" aria-hidden="true" tabindex="-1"></a>    <span class="fu">ylab</span>(<span class="cn">NULL</span>) <span class="sc">+</span></span>
<span id="cb151-85"><a href="#cb151-85" aria-hidden="true" tabindex="-1"></a>    <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="ot">-&gt;</span> p</span>
<span id="cb151-86"><a href="#cb151-86" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb151-87"><a href="#cb151-87" aria-hidden="true" tabindex="-1"></a>  <span class="fu">print</span>(p)</span>
<span id="cb151-88"><a href="#cb151-88" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb151-89"><a href="#cb151-89" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb151-90"><a href="#cb151-90" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb151-91"><a href="#cb151-91" aria-hidden="true" tabindex="-1"></a><span class="fu">map</span>(<span class="fu">c</span>(<span class="st">&quot;deselected&quot;</span>,<span class="fu">paste0</span>(<span class="st">&quot;pos&quot;</span>,<span class="dv">1</span><span class="sc">:</span><span class="dv">6</span>)), plot_amce_mm)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" 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</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="data:image/png;base64,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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.
Warning in logLik.svyglm(x): svyglm not fitted by maximum likelihood.</code></pre>
</div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img 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" 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" class="img-fluid figure-img" width="672"></p>
</figure>
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</div>
<div class="cell-output cell-output-stdout">
<pre><code>[[1]]</code></pre>
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<figure class="figure">
<p><img 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" 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<pre><code>
[[2]]</code></pre>
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<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>
[[3]]</code></pre>
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" 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<pre><code>
[[4]]</code></pre>
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<figure class="figure">
<p><img 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ZVIF9Lya6Bh1zyGQK1AoMZgCNSeBgKttBae1y82jsIHW/MYArUCgRqDIVB7GggUO9J7BgJVgyFQt+wQaH0gUM90ItDYOAHCRPsug0DpQDJtAYFWoOvvHzCgfZdBoHQgmbbo83sDAIBGgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARbGdXga53AwMGtO8yCJQOJNMW2JHeCnakNwZjR3p7GuxID4F6BgJVgyFQt+wQaH0gUM9AoFYgUGMwBGpPA4FCoJ6BQNVgCNQtOwRaHwjUMxCoFQjUGAyB2tNAoBCoZyBQNRgCdcsOgdYHAvUMBGolaoHGm3xJBFo9kZ8snQv0eCeRnPuQ3H90k9x6+e68iDeSZP3bB14O2zsQqBUItJPkEKiWyE+W0AT6ZJvdXH/HGDHmNzc+9HTkfoFArTQh0F8QsuBoHbcsAs2frdppINDyLvzhkEqTyHLzbvqI/FtsYfKIwyGNOL5TFhEAEKiVBgT6i1/k/ibjddySCFQ5W7XTQKClAiXm3EqpHlkvnbRDrxkiRsKco2JECECgVvwL9Be/yP9Nxuu45RCoerZqp4FASwU65l4cJ+fF3a3yCKJRLs6piAwMCNSKd4H+4hfK32S8jlsKgWpnq3YaCLRMoLLJOcr0qPfQRcSTbXF59HAYZB8eArXy9NOfFvhFABSPaskoCNT6CpykLjgh9uTJnyvRMc/al0U96hFTPiQfGhCoFQg0UCDQOCgRqGyA5tqXmh6zq6Ij0XUfQaCS6AQacRceE+ldaakLv5wT6cUV0DkClRGk5ZlcOKCj8BCoZNkF2uYgEgTqSkuDSEspUDHAPkegWYScB7r+v+mKDQMI1ErU05ggUFdamsa0lALNdKlcA53yGfPXlAjC/StJ8tJdDCJlQKDtTaSHQF1paSL9Ugp0nE1Jyo/C5wU6LkxawjSmDAhUDYZA3bL3YinnUgp0lOufl88DHRXmhRYfCQII1AoEagyGQO1pINDCW8yufBpXIuUihGL5us7wgECtQKDGYAjUngYCLbzF3AXO451ko2QtfC7icJhcTdP7wzB78BCoHQjUGAyB2tNAoIW3mF92RPyo78akRdzhl0aDHEKCQCsQtUDjTb4kAq2eyE+W0ARash+oHvHJi0nywtUw/QmB2oFAO0kOgWqJ/GQJQaB9AgK1AoF2khwC1RL5yQKB+gUCtQKBdpIcAtUS+ckCgfoFArUCgXaSHALVEvnJAoH6BQK1AoF2khwC1RL5yQKB+gUCtQKBdpIcAtUS+ckCgfoFArUCgXaSHALVEvnJEoJAj+8Mk2TjbX6ndBqTGoGyxioQqBrcZHJMpHelJYEu4UR6MXeer20vKWusRaCssQ4EqgaXRpt3AIJABUELVJ4/CFR/i0SZG3fT4/cTY1ljJQJljQtAoGpwWfScPSghUEHIAs3OHwSqv8VxVqd4y7CZiBKBssYFIFA1uCR63i7oEKggYIHOzh8Eqr3FbA9lRtl2dkoEyhoXgUDV4GL03Do8EKggXIHmzh8Eqr3FJ9v50hxlZY2VCJQ1LhKdQOsXIqxfvrEZPj1hL1UZLfWrctams/PWJ9SqnFSEtEgHG2MvLWtcHoGyxhkQaGtAoIvR2XnrE6pASVvzZjbGXlpUTolAWeMi0QkUXXhDMLrw5eTOH7rw2luklY9EneJrJoHmIlDWuAgEqgY3OYgU7wzWmAVaYxCpneOZZQlBoHy8iDYtTQKdRaCscREIVA1uchoTBOpKS9OYKtMfgeacWVrWWIlIUda4AASqBjc5kR4CdaWlifSV6YtAs7Ymu1FW1liNkGAaUwYEqgYjuVv2oAWapYFA9WlM+ZlLZfNA1QgJyhpnQKBqMJK7ZYdAHbJ0LtDcsPp5w0okJQJljQtAoGowkrtlh0AdsnQv0MMh3Xzp+I5cC18sa6xEoKxxAQhUDUZyt+wQqEOW7gWaTsVeS6zNWVrWWIlAWWMdCFQNRnK37BCoQ5YABJo+ujmk4+ryTsl+oEoEyhprQKBqcJPJMZHelZYEunQT6XsGBGoFAjUGQ6D2NBAoBOoZCFQNhkDdskOg9YFAPQOBWoFAjcEQqD0NBAqBegYCVYMhULfsEGh9IFDPxCzQB6uDNU+p5gGBGoMhUHsaCFR/i6KOnNhdqWwUXotAVU4VXwLdGwyees9TrjlAoMZgCNSeBgI1VeWUa5DMVTlZBKpy6ngS6OOLK88MLvvJNY/IBKruQgKBuhKkQM1bzHg6nOqJqocWJtLnFhWVVuVUIlCVs4AngU4Gp/cGZ/zkmkdcAtX2wYvoyGtn74VAqydK525y2MXhVEQ/T/ltQUrXwisRqMpZwJNAdwdrD1azPvxn764OBmf3d3mb9OENcu/Z215+T1QC1XdijufI62dfOoHO22a7g8Opinaejndy/fWy3ZiUCFTlLOJHoKQH/9bRdTmM9IAIk3Dq75hAJ/yenw5+TAIt1AKJ5sgdsi+bQOcWemn/cCqjnacn2+d+TEvGMUeWVeVUIlCVs4gfgZIe/D7/h0BMeup2enSLS/PxRdIWpfdW3vLwi1yKytWnfuGxFmjjjbvTQlE5j3R9LhVafedqUblshIi2OUurcpZHoCpnhheBEmVe5s1Qem8ixuP3mEDlpVE/l0gh0ECBQJ1p9Z1rAp0mdFTo85t05L20JpISgaqcRbwIVFz+3OWO3BVdedL2vEzcKlqeD1Z5+3Qx0IU3BqMLb0+DLrx2nsbZqJChqJwSgaqcRbwIVLQuedOTN0cpdBCJWFTiY55oTALFIFKPBdqTQSQJvexZLtB8BKpyFvEhUKJMyeV01uZceoFiGlOPBdqTaUwCY1VOJSJFVc4CPgQqRt0ppJuut0C9DB5J4hIoJtLHJdAlnEgvMFblVCMkmMaU4UOgu3J8aMKG2uU1UGbSmU69EJlAVSBQV4IU6MJ0L9DcsLqhKqcaIUFVzgwPAmWDRfLW2mwUfsJ69LticpOc5LQYEKgxGAK1p4FAy6tyEk1uza/KySNQlbOAB4FOZlc3d0Ufns4D/eUqEyjp35++naYf+dmtCQI1BkOg9jQQaLEq54WD9NEVNqpuqso5i0BVzgIeBLo7m+E5kc5k10O/q6xEOrv4b4JA5wRDoPY0EKj+FsX2SrxFWVqVU4lAVU6dxQVKdJld5SSNTypTuhZ+RV0Lf+rNhX8RBQI1BkOg9jQQaLEqJ93g84IQYnlVznwEqnJqNLgjvefxIwYEagyGQO1pIFDsSO+ZBgQqF23mtmfyBgRqDIZA7WkgUAjUMw0IdDIYPL+fpvdWG9ggNGqBxpt8SQRaPZGfLBCoX3oi0Gxhko95SxoQaCfJIVAtkZ8sEKhfeiJQ0vh8lejzr1/3708ItJvkEKiWyE8WCNQvvRFoc0CgnSSHQLVEfrJAoH6BQK1AoJ0kh0C1RH6yhCLQbG+Q0mlMagTKGqtAoGowkrtlh0AdsgQi0GO59qi0rLESgbLGOhCoGuye3L45T6hH7iN7bwVaelr7JdCxWFpUXtY4H4GyxgUgUDXYOXmF7SEDPXIv2fsq0PLT2iuB0gWcQo9lZY3zEShrXAACVYNdk1fZoBwT6V1pSaDFE2Q4rX0S6JPt9R/zK5ylZY3zEShrXAQCVYMdk1cqkQOButKVQE2ntU8CHSVbYoiotKxxPgJljYtEJ9AmShXWr6TYJE28w8YJtipn12fzF2GdUK0qJ7flodq+1PRYEoGyxhkQ6KdB/JHlaOIdNg4EaqbrjyCPLlDWqCy0L/N6zEWgrHGR6ASKLrwhGF14exp04fW3OOJb0c8RaC4CZY2LQKBqMAaR3LL3U6C9H0Ti40bzBJqPQFnjIhCoGtzkNCYI1JXOBNrzaUxClSXXQGVVTiUiRVnjAhCoGtzkRHoI1JXuBNrvifRiYZGo0lFW1liNkGAaUwYEqgYjuVv2Xgi0eiI/WQITaNk80HKBoqxxBgSqBiO5W3YI1CFL5wIViB65cSVSFoGyxgUgUDUYyd2yQ6AOWQITaGlZYyUCZY0LQKBqMJK7ZYdAHbIEJtDyssZKBMoa60CgajCSu2WHQB2yhCbQCvuBoqyxBgSqBiO5W3YI1CFLKALtCxCoFQi0k+QQqJbITxYI1C8QqBUItJPkEKiWyE8WCNQvEKiVqAWKifSutCTQyicIAg0SCNQKBGoMhkDtaSBQCNQzEKgaDIG6ZYdA6wOBegYCtQKBGoMhUHsaCLTwFunuIFmd4tJpTGoEyhqrQKBqMATqlh0CrU8IAlXqFJeWNVYiUNZYBwJVgxtMbt+uaYHkEGiVNO0ItOqJDkCgh8P1q6RZuc3WZpaWNVYiUNa4AASqBjeXvMKGoe7JIdBKaVoRaOUTHYBAxbZKfBuR0s1ElAiUNS4AgarBjSWvsmW9c/IUAq2Upg2BVj/RAQhU8GSb6tFU1jiLQFnjIhCoGtxU8kpFk1yTs2AI1J6mBWPVONHhCJQXMjaVNc4eQ1njItEJtOuyho6EWaPRH8FW5axF9UqbrdDAOyyUNaZ8MqTqNJU1LolAWeMMCLQdGv2rCAAItAEaeIclAh0lyfr/mRqrcuYiUNa4SHQCRRfeEIwuvD0NuvDFLvzxza8OEzrSbhRoFoGyxkUgUDUYg0hu2SFQSfUTHYZAKfdpD93cApURKGtcBAJVgzGNyS07BJpR+USHI1Aixs2D0rLGSkSKssYFIFA1GBPp3bJDoDOqnuiABMoanWVljdUICaYxZUCgajCSu2WHQB2ydC7QXKOT6LFsHqgaIUFZ4wwIVA1uMjnWwrsS00T66nQv0Nyw+nnjSqRcBMoaF4BA1WAI1C07BFqfAAR6OBTD6tSIpWWNlQiUNS4AgarBEKhbdgi0PgEINP2EX+tkk5TKyxorEShrrAOBqsEQqFt2CLQ+IQiUb/AptwAt3Q9UiUBZYw0IVA2GQN2yQ6D1CUKgfQICtQKBGoMhUHsaCBQC9QwEqgZDoG7ZIdD6QKCe6USgsXEChIn2XQaB0oFk2gICrUDX3z9gQPsug0DpQDJt0ef3BgAAjQKBAgCAIxAoAAA4AoECAIAjECgAADgCgQIAgCMQKAAAOAKBAgCAIxAoAAA4AoECAIAjECgAADgCgQIAgCMQKAAAOILdmCrQ9WY2wID2XQaB0oFk2gIbKlvBhsrGYGyobE+DDZUhUM9AoGowkrtl74VAqyfykwUC9QsEagUC7SQ5BKol8pMFAvULBGoFAu0kOQSqJfKTBQL1CwRqBQLtJDkEqiXykwUC9QsEagUC7SQ5BKol8pMFAvULBGoFAu0kOQSqJfKTpXuBPtlOMtbf8XQ4nQGBWoFAO0kOgWqJ/GSBQP0CgVpZWoF+k9BY8grRSy5Q7ePvkUDPfejpIAIAArUStUAXmEj/zW/aDAqBVkhjyWM8QfrHD4EGCQRqZUkF+s1vWg0KgVZI4yjQwsffY4Hev5IkL1zltx/dJD37l+7Sm4fDzT99MEySjbcLT42T88d3kmSdvOgTEnHhgEUfsLBRsuXyhhyBQK0sp0C/+U27QSHQCmncBFr8+Psr0DG/Hsq0Nx3ya6PXUqrEjSuGp8bJV3bYvat32A/izuMdfkH1yXarF1YhUCtPP/1p8HwzKjy96YJAPeWtQdef5CK09iGdEHvyiNOkC/RwmLxycPx+Qh8ltzfvpp/fZKNL5A55Jn20U3yKOPfcT4gzeSN0LB7jnk1ES7QdIFArEKhvPL1pCHQhWvuQCgKdjcKfT1l3nPxLZHiNdr+5/Ub0MaJMpsTDIfWj8hRXpozgrxV9+HZ78BCoHXThjcHowtvToAs/ZxrTeWk/TnabNSO5OEWnXH1qzG0qu+tMmrwP33IPHgK1s5wCxSCSpzQYRJp/DTRvvOz24ZDEsH/ko+pTvNWapeKtTtaHb7kHD4HaWVKBYhqTnzSYxlRHoOIpdkMTaP6pUoE+2SbubLkHD4HaiVqgmEjvCibSz09UPbStFmg6Wn+n7R48BGpnaQXabfKlF6ieyE+W4AQ67xpoTqD6NdAygU6TrSl/oj0gUCsQaCfJIVAtkZ8swQmUD6uLwXgx1E5seT5VBao+VS5Q0od/f2bjdoBArUCgnSSHQLVEfrKEJ1A2DzS9P+RTkZR5oHmBavNAywRK+vAvtr1MFAK1AoF2khwC1RL5yRKCQBN9Imh2U1uJlBeothKpVKDTpO0ePARqBwLtJDkEqiXykyVAgapr4d8gj74s1sIrAs0/ZRAoSd1yDx4CtQOBdpIcAtUS+cnSvUAbpIONniBQKxBoJ8khUC2Rnyy9FmjrY/AQaAWiFugCE+krBEOg9jSWPJVPEARq5VHbk0BTCLQCEKgxGAK1p4FAWxLoKGl/CAkCrQAEagyGQO1pINCWBDrmGyu3DARqBQI1BkOg9jQQaHBljY89ehYCtQKBGoMhUHsaCNS1Kue4oR75/Sse5zpBoFYgUGMwBGpPA4EGJtD84vvFgUCtQKAqs12CINAKaZoTqHW3LIfDqZ6oemhgVTkh0JaBQBVy+1RCoBXSNCZQ+36tDodTPVH1UAjUMxCoGhxV8vxO6RBohTRNGatCxYA2D2cO1s1EctWLZ6vaNw9YF55uUTdMNt6ZU/C4pMZxSsOHpeF85b03hUKgViDQHEqtHgi0QpqGjFWlZi3SfikAACAASURBVFWLhzMPq0Bz1YvlWiIqUiHQrxH1kVeYCx6X1DjOth5JCuEQaNvEUJXTRP1ajd1R+80FUJXTQtcf6YJ4+hTsZY1n1YvFk2z/ECFQuovdH+YVPC6rcfxkm7ZEj98vCUcXvmUg0Hao/eYg0Ibx9ClYyhrr1Yup3Wbbzk8TWXjTWPC4rMaxHMEfF8Mh0JZBFz7H7K+rgeRaNLrwSiL1rnIiuj+cecwva6xWLxZ9+FEmwSlrNc4reFxW45iXOE5FsXg1HAJtGQg0T/7PFgKtkAaDSNZroPltP9mzPEQIVLFjSbm5ss1Bc5IuhEOgLQOBKuT+bCHQCmkaM5aLP8MXKC2tKZSoCtRY8BgCDRwIVGX2ZwuBVkjTnLEc/BmBQKfJllDcQi3Q/BonCLRTohYolnK6EvxEeifCF+iT7c3/yh/JC3ROweMygaqShEA7BQI1BkOg9jQQaD2BpqNzP8oVOp5mo+/GgsdlBZLkoH2JbyHQloFAjcEQqD0NBFpToFO5x4gi0DkFj8sEysPpyqStkhbod5zecvmb85eqMhCoGgyBumWHQOsThEDVqpy6QMnz3JmKQOcUPC4t0SlXIl0ohLOt67fc37n25nwlqgEEqgZDoG7ZIdD6RCDQbD28KlBzwePyGsdsLTxfLK/9huObHmt/QKBWIFBjMARqTwOBBrcjvU8gUCsQqDEYArWngUAhUM9AoGowBOqWHQKtDwTqGQjUStQCjTf5kgi0eiI/WSBQv0CgViDQTpJDoFoiP1kgUL9AoFYg0E6SQ6BaIj9ZeiZQnxWKnYBArUCgnSSHQLVEfrJ0L9BDMUMz+eq3F7Yfr1DcVP3jKkCgViDQTpJDoFoiP1kCEqilqnEF8ruOdAQEaqXPAi1s6BPOkfdPoC67J+USeTiYQATKp7Uf/+7Kogb1u6zdCQjUSo8FWtxSMpwj751AnfbvzCXyfDiLJqoeahCo3BlkASDQGOivQEs2NQ/nyPsmULcd5H0fT1ACzWpt5CoWW2sUi+B8hWLRhb9/JUleuLrQu6oPBGolaoHOGwEtK6sTzpH3TKCmGkbLN5E+J1B14491fj3TWqO4UKFYbmCfFTpuEQjUSkBVOesXVuyCtj6NJqpydv3ZLYSH998EWlXOvEBl0czZTnXWGsWj5Dy7natQLLO8ciAebxEI1AoEWpO2Pg0IVMPD+2+COQJley0pFYttNYrljkrsibxAeVDrV0UhUCvowhuPBF14exp04ed04alA1WodthrFJJrvUUfJCbSr8SQI1EpvBYpBpLm/3lMayyDSsgv0fKrWi7OW2JzSny/wOfg5gapl5NoDArXSX4FiGtO8X+8pjWUa03ILlKsvX7HYKlA22E63Vj6AQOOgxwLFRPo5v95TGstE+uUWqFKC2NwC1dx4/G9v8M3sIdAY6LNAF0sOgVZIY8mz1AJl80D1a6CWGsWCMW2N4hpoDEQt0HiTL4lAqyfykyUkgYqVSErFYluNYvlq9jM/Cj/K1UJuEQjUCgTaSXIIVEvkJ0s4Aj2+f4VP2tTmgc6vUUycSW8/2hFdeFqheDYPNL0/xDSm0IBAO0kOgWqJ/GQJQaD6bkzqSiRrjeLZeJKoUKysRGp5YyYI1AoE2klyCFRL5CdLQAJ96W25H2iuYrG1RjG/vS7mMbEKxVgLHzQQaCfJIVAtkZ8s3Qu0X0CgViDQTpJDoFoiP1kgUL9AoFYg0E6SQ6BaIj9ZIFC/QKBWINBOkkOgWiI/WSBQv0CgVqIWKCbSu9KSQJdvIn2/gECtQKDGYAjUngYCXVygnRcvNgOBWoFAjcEQqD0NBGpeymlbwC6e58WL82vowwECtQKBGoMhUHsaCHRRgYoFmxCoBAJVgzsTaMn2QOEceX8EWroLkwQCnQMEWgoEqgZ3JdCyDSrDOfLeCLR8H1AJBDoHCLQUCFQN7kigpVukh3PkfRGoYSd6CQSaqlWL0/tvZFvOs+dl7U36uk9eTHIVPUIAArXSU4GWF+kJ58h7IlBTLSQJBKpWLU7viJXydAc7XaDfysUFAgRqJZCqnPWLNHZFW5+Iv6qcXX9ii+LxQ20Ac1VOLlClavGUlTM+vsM0qXXhE7ph3aMdsTtoGECgViDQmrT1iUCgEo8fagMUBJrMyG0BKvdFZtsvEWluFQW6xV/fTfGOciBQK1F34c3JZ39+DSQ3xNeLXooufGV61IVXBapULZZBpQLlcV1VPyonKoE+vjgQPPtmyZMrb6Xp3uDMQsdWQk8FikEky6/3lMaTP/skULULrxXdJML83b//8MWkRKD8aQjUg0AHRU9CoHWTl/1hh3PkfRGoZRpT9UQeDiYGgdKBdgYEamIBgT71Hrtx9MvVwVrhSSrQBuitQDGRfu6v95TGMpG+eqLFU6SBCjQvxCnp1r/0j//8+7IuPATKWVygtKV5el9/EgLtU/L+CNRTIj9ZwhOoUpCYX/s0XAOFQDk+BPpgld18eINeEL3Nn8x14e9dGgxOvs7ihGh3C03WyocLgXaRHALVEvnJEp5AlarFshbSdAiBGvEn0Mkqux66cjlVBbrHr5Oukc7+dd4uXaB9GrVAsZmIKy0JFBPplarFT7aT8wfp8QdD9Rrod1IIdIa3LvyD1cHp2+lnNwZUjjmBksef3z+6NaDRe7zlOSl0+asfLgRqCoZA7Wkg0MorkS6kWXHizffppFDxPC9eDIFKFhfoZ7cGg8u0W86tuEutmRMob4YeXacxog/v3oOHQM3BEKg9DQRacS28WONOR+FfuMr68/J5XrwYApV4mcZ0VhoyFc3LmUCzxym8D7/ICBMEagyGQO1pIFCU9PDM4gI9+dy/pjkrsguiM4GqtmR9+AV68BCoORgCtaeBQCFQz/i4BqrcZTdMAn18kbhzgR48BGoOhkDtaSBQCNQz/gRapQWa7q68tdAcUQjUGAyB2tNAoBCoZ3wJtNI1UPrs2mSRBZ4QqDEYArWngUC7EmgrtTxjFqgchSfCVEfhd7kvxaR60oe/pRi17uHGLNB4ky+JQKsn8pMlDIEe33+DTl166W0PjuOj8nJPvBm8lmfTRC3QufNA03urQpu7K8+or6t5uBBoF8khUC2RnyxBCPSTbEc7DzOSDAJVVog2R9QCta1EEv32ScneTXUOFwI1bIcBgVZI49NYi29LEoRAx3TS5wFth17xYFDDvFAItEhBoOnDV4knn5uzFp4/s0gPHgIt3ffOW3JzNASqJDKfh44Opyr6eZJbyxOOR4Wed20g0KYpercWSy9Q45bAEGiFNP6M5WNr5gAESsw2k+bh8Bwrxpmry3k43PzTB7OVSfmnpsnWdJhsvFMs3Sm68I9usiuraZqVomuaZRDoQmPwEKi5KAUEWiGNN2N5KQ4SgEDV+u6/Z//m63IeDjeuZFsqq09Nk68N2bbLhdKdXKCyWsgWBOqRhwtuFBpIUbmq1C9J1iELvVN/ReU80vUnuhDNfCRaUbnieLlal3NWfZOKVivZSfdt+kNZ6U5Rke48i6UvRBfeD7tl5T9qAYE2x0LvFAL1TTMfiSbQUXYFNEOpy6lW31Semooxp5LSnfR5ufcIUycE6oe9weCs8zJ4RtRdeA8T6Wd/X4VgdOHtabxNpDefB4+HUz1R9VDtLUqBEsOJ/rZal1Opvqk+NU3yvf+CQMl9eeEUAg2HZRcoBpEWSuNvJZIHf4YpULWsnLJtnfrUNMkKH+ulO0ULNRtagkCDYekFimlMi6TxuJRzcX+GIFD1GujISaDF0p08630+/PTyAQQaDhAoJtIvkMajQPsxkV4dhecCzc/k1ASqluyU1ZMKpTullo//jU5wOg+BLs7RYpc+MyBQYzAEak/jU6CLE4BAZeFNzohdA827ThGo+pQQaFnpzny7dkxbqxBofv95h4lI9y7R5Ud7Cw7BpxDonGAI1J4GAp2zEil9tE1v5+tyaqU7lKeEQMtKd45zRT/YTwh0MYGKPe0g0AaTQ6AV0kCg5Wvh/8D2ZErk1M+sLqcmUOWpTKDF0p1iFJ7GPtoRXfjveHqvc99cC79Dp7JAF1mBqW0KugAQqDEYArWngUCLb1GM9bBKnLx9mavLqRWPyz8lr4GWlO5UViKxBCO5lqlRIFArUQs03uRLItDqifxkCUKgRKE32X6g35azknJ1OfXqm7mnlFF4tXSnXAtPYtfFPCZWy7Np4hHohPfjH6ySH5PB6Y9/uir3YUrThzfInWdv87C1yerg1N+znv9l0YV/eIPcefbNQnC1w4VAu0gOgWqJ/GQJRKC9IR6B8v3nScNyjdXw+O5sJ1C5LShrck4GXyb3nvqnvEAfiOfX9OBqhwuBdpEcAtUS+ckCgfolIoESDa6J+sSTAVug+fD6gIY8vkjvHN1iTVTy1Onb6W+UQaTdwRn2fCG42uFCoF0kh0C1RH6yQKB+CVqgs1F4UePoqf/3omhm8kd4e1SOtLOfoqefF6ioyckfUYKrHS4E2kVyCFRL5CcLBOqXmARKDChuSUuyBunR9ay6MWmdTga83ZoTKLl5Slz/TNXgaocLgXaRHALVEvnJAoH6JWiB6qPwpOHJH+Id+ZRXhM+Jljwrn8p34WmPf3Dytf1UsXLVMX4ItJPkEKiWyE8WCNQvUQmUSJHbsaZAWYkkWjxpHwKNJjkEqiXyk6V7geb2B6ETNkv2V46JqAS6l42kqwLNjweVCpTc/ZdXWf//cf3t6aMWKCbSu9KSQJdvIj0EuiiuAiW2/L9Xmf/khU5xDTQ/Jckg0JTdfuo9h/n10QqU7t0DgbpiSlNzRyQItChQD8XggyEigbIh910mxIloifJR+N18x75EoLSZSh9iP3f1qwD2w41UoHz3SAjUEUOauntyQqAQqG8cBcqU92CVepGOCj2/nz68xCxIHjt9O00/WhVz7KVAv5Fmo/D0+YfXxaT6WXC1w41ToG77l4dw5FWzdyHQ2p8qBGoRqFjErpYyzlUtLjx1ha3iZOQqHndF0AKdTWOaXb3c4yNFJ5/J7dIkFxedTXMty112wVRZicSEnA+udrhRCtSxgk4AR145ewcCrf+pQqDVBKqUMs5XLdaeGhsqHndFPALlnXf6KFuP9PG7RJ+viV44W97O53pmAj26QV8l18KvzqJzwdUOt72qnPXrKLZMa59EFexVObv+uGrQwefXFlpVznKB5ksZK1WL1afIvVcOROFipeJxVwQs0DlUv4DpAQh0RmufRBUg0DgoCDQbhKfj7yWljJWqxWVVjvlmyUrF466AQK2gC28MRhfengZdePM0ppxAc6WMJVKgSpXjWX9drXjcFRColTgFikGkBWlpEGnB46mdJQSBlnXh1T1Ac1WLjTXm1IKdXQGBWolUoOJvPcYjr5i9F9OYqifykyUKgearFkOgBSBQNbjJifRxHnm17L2YSF89kZ8sMQhUqVo8R6AhzCeNU6CtEq1A404eqkDrpoFA6wpUrVpsrHLcUtlNCxCoFQi0k+QQqJbIT5YIBKpWLdarHJ/PXqRUPO4KCNQKBNpJcghUS+QnSxQCzVctLlQ5fuUgvT8UM0RnFY+7AgK1AoF2khwC1RL5yRKBQNWqxdr40ng2AUqpeNwVEKgVCLST5BColshPlhgEqlQt1mc4FdbCy0Xy3QCBWolaoNjOzpWWBLp8E+n7BQRqBQI1BkOg9jQQKATqGQhUDYZA3bJDoPWBQD0DgVqBQI3BEKg9DQQKgXoGAlWDIVC37BBofSBQz0CgViBQYzAEak8DgUKgnoFA1WAI1C07BFqfAASar8rJ58Zne4FkM5yebG8eaNU77XSyLygEagUCNQZDoPY0EKiDQA+HW3r5YzsQaJhELVCevPoOQuEceXQCLf+QMZG+KFBVh2UCHWs7L4ULBGolfoHW2MMynCOPTaCGDxkCdRDo8c7mAQRqBAJVg5tOXmcX9XCOPDKBmj5kCNRBoLQHXxToo5uJLGI8Tbamw2TjHaWysejCf36HPHLhYMT3G1FrIvsHArUSu0Br1fEJ58jjEqjxQ4ZAHQRKe/AFgYqtQ9bpJqDT5GtDdmU0X9mYC/SQP7LxLS5QpSZyA0CgVlqsyjmjflnHdungIylgr8ppoutPryYNfoZtUKjKaRPo8Q6vWqwIlG9e9/nNROxZT+78Qa1szAR6vJNs3KWPlNREbgII1AoEWkIHH0kBCDQOzGWNRZNRF+jh8LwaR+/K7ZPZlspTUQteqWw85s/wbGMp0FxN5CaAQK2gCz8neS3QhW/teIxZQujC2wQ6ZT1yVaBZAQ+2x53QpFrZWGxTvyV/yzVDuWSvQKBWYhcoBpGcwCDS/ETVQ2tfAx2xB1Tp5aaI0kufvDmqFuakAp0VShKDSFq5ZO9AoFaiFij78lb3Z0BHHplAXacxLeNEeotAn2yfn90pvIrdmCNQ+SIINBTiFygm0jvQ0kR6CDQnN+473oOv1gLNh6AFGiY9EGhDySHQCmkgUItAc+WJuRdHZdLTr4EygaqVjZVroPwpCDQAIFBjMARqTwOBWgSaja9T6Z3nG4nwOEV6o8yZ52eVjJXKxsoo/DSBQAMBAjUGQ6D2NBCoTaCHw2Tj/yc/f3dFbC4ix9HnzQPl4lQqG+fngf52CIGGAgRqDIZA7Wkg0DnTmNTyxHxy5zjb0m7eSiTRaM1XNlZWIm3+AAINBAjUGAyB2tNAoFaBpp9/8CK5/cK3eR9duLG4Fv4NEvSyWAsvgvKVjXNr4deztfAQaOdAoMZgCNSeBgLtZEd6dXypOSBQK1ELNN7kSyLQ6on8ZOm7QOXiztzs0kaBQK1AoJ0kh0C1RH6y9F2gU7Z7SHp/2NL29BCoFQi0k+QQqJbIT5a+C5R03TnyImnDQKBWINBOkkOgWiI/WfouUNL4pGNNX73ajj8hUDsQaCfJIVAtkZ8s/Rdou0CgViDQTpJDoFoiP1k6F+g4yaYpJXKgnO1Gl0dOO6Lz4b/SUlvSDQjUCgTaSXIIVEvkJ0vnAs2Gx+mMdzHQM9YrbmQbg2ZTRUMFArUCgVZObtn1CQJdJNFiLxenpnuB8p2OU2rNvxEune1BNwvii5ICb36mEGgFohZoqxPpbfuOQqBFWppIL09N9wKV+yUd7yRXd+R+8fqQudxZubFacN6AQK1AoMZgNdq68z0EWqQdgWanJgCBZnt5nvtQdN2nvJueq1DMBDqVOyXzgXW+0rO0oHGHQKBWIFBjsBJtr70EgRZpRaD5+nQLpHE8HO0tioug1KPCpWPWqc9XKFYFeic3tbO0oHGHQKBWOqnK6YsTpaUq6xeGDICS96aeqOpVOQPixImuP1fPlLxFtSqnWKVOu+d8ZztZxThXoVjpwk+T9ask6g6TZWlB4w6BQK1AoGFQ8t7UEwWBhkDJW1QFysfc2cCR3Db+fKpVKFYEOrtoumUoaNwhEKgVdOGNwejC29OgC6+/RdZx5x15sYn8Nb1CcdkgkhRoSUHjDoFArUCgxmAMItnThCDQoAaReMd9PKsJP+Kd9nyBTV2gx7/79x++mHCBltTj7BAI1AoEagzGNCZ7miAEGtI0Jl4wk7uRipJPYpon0E9eFM9AoAwIVA3uT/L5/oRAF0q02MvFqQlCoONkS67VJIrkNZBKixjLQaRk/aV//Off7ygC7XjwSAKBWoFAO0kOgWqJ/GQJQaCHw/PTrJzmeV4DSd1BPi9Qfu1zdg20pKBxh0CgViDQTpJDoFoiP1lCEOjxzrkfZRvHb/6gpEJxXqCyiud0mBOoGt4hEKgVCLST5BColshPlhAESuwnJ8DT/Y+lSnMVilWBJucP0uMPhvlroGp4h0CgViDQTpJDoFoiP1mCEOh0NvQzztYS5SsUK9dAx2Id0vt8zlNJQeMOgUCtQKCdJIdAtUR+sgQhUNKolB3v6WwUPVehuDgK/8JV7s7SgsYdAoFagUA7SQ6Baon8ZAlCoD0CArUCgXaSHALVEvnJAoH6BQK1ErVAW51I7zX5kgi0pYn0WRYI1C8QqBUI1BgMgdrTQKAQqGcgUDUYAnXLDoHWBwL1DARqBQI1BkOg9jQQaIMCPe68ZBIEagUCNQZDoPY0EGjJWzy0zX+3bPMppjndv9L5ek4I1AoEagyGQO1pINCStzi2baJUSaAhLIiHQK3ELFDL9kiLJV9ugVb8aCHQ0on06y8u5D4INCIiFqhtg86Fki+3QKt+tBBo6VLOzcVKcUCgERGvQK1bxC+SPF1qgVb+aDGRvnQzkS1Rm5Py+Z1hklw4GPGacbxqsfDr/StsEWea1fIU6mT/jkVVTvWpluseQ6BWohWovUjRAslZ8NIKtPpHC4EWBUpNJ3f5ZANKlI1vcYHyqsVcoONsI/o6Am217jEEaiXaqpzzKiX2gZpVOasXluyKdj621tGrcqq7ghCTbtyl9YmVqsVMoEStrxyQZ6gfSwQqu/C6QFutewyBWoFAAwUCjQNdoNx7siiH3I5pLASaq1rMm6Gy9nFlgbZa9xgCtYIuvDEYXXh04e3o50kIb8TNJitvkhbjtbxOz6tjRDUE2mrdYwjUSrQCxSDSImAQaX6i6qH6eRJtQm66mSXFIBLXHY1RCsfVEGirZTshUCvxChTTmBagpWlMlemNQGkVjyQb38laihBoZSBQNRgT6d2y92IifWV6I1Ax6s6qdBw02AJtp+4xBGolZoFiKaczWMo5P1H1UO0tjuSoDh/ukddAuQ3zAnW9Btpq3WMI1AoEagyGQO1pIFD1LfLBInFrazZsNE10gUrViilNcnC9RKD5p1quewyBWoFAjcEQqD0NBKq+xVwVuZHow9N5oL8dFgXK5oGm94f8WqmcLqoI9Dup/lTLdY8hUCsQqDEYArWngUDVtziazcvkjU5xTXTzBwWBypVIYtCe8crOTKCsvvyW9lTLdY8hUCsQqDEYArWngUCVt3g4nF2bJE1H6ka6Fn49WwufF2huLTy5/Qa9fZwX6PFNbtf8Uy3XPYZArUCgxmAI1J4GAq32FkPYWskBCNQKBGoMhkDtaSDQ+W9RLrXMbc8UE50INDZOgDDRvssgUObZYJrQkSI6VNTomvWmgEAr0PX3DxjQvssgUObZIFuY1Ohso8boc8VRAED40CGg5KtXo/QnBAoAAK5AoAAA4AgECgAAjkCgAADgCAQKAACOQKAAAOAIBAoAAI5AoAAA4AgECgAAjkCgAADgCAQKAACOQKAAAOAIBAoAAI5gO7sKdL0bGDCgfZdBoHQgmbbAjvRWsCO9MRg70tvTYEd6CNQzEKgaDIG6ZYdA6wOBegYCtQKBGoMhUHsaCBQC9QwEqgZDoG7ZIdD6QKCegUCtQKDGYAjUngYChUA9A4GqwRCoW3YItD59FehxVxWVIFArEKgxGAK1p4FAC2/xt8Mk+YpX492/co38+2R7/R2fWasAgVqBQI3BEKg9DQSqv8UpLWLstQj88U4CgQZLvAL9IiHOI6+UvRcCzUPPlzmRh4MJQ6Bjz81PCDRsohXoF7849y9yseQsGAK1p6n3/535fPVHoKNky9NBSCDQkIlVoF/8ooNBgzjyitl7JlDL+eqLQFkHPjn34TTZmg6TDWK8RzeHSfLSXf40vbN+4WBEjXg4PPchfUyKMRd4ONz80wfk3sbbKW3SUq7xOPIMb9/693Tpm2vhd+hAoGpwM8m/+EUXg4Zw5FWz90ugtvPVP4F+bUh/pkSjQoApFSO7vfmDEoHmAw+HG1f4vS1NoMc73LYtNUchUCtPP/1pEHyxJbp+n5UpCLTrAyoDZ+rTE2JPHnmeeNOQiHTzbvoHIrrkwkF6/H5CfUfubNyld5KiQJVAKtpXDtJHO1TBahd+zFue02SzjalNEKgVCDRQINA4MAmUtxDHYkCe/RwnXJnjEoEqgUSgTJOHQ/qUIlDRh2+nBw+B2kEX3hiMLrw9Dbrw5YNIU+5K2ePm3pPWI61NXaBqIBendKYiUB7Y1oBS1AI92veVaR6RChSDSIuBQaT5iaqHmgTKGopElZJzHwoRshhdoEqg1jhVR+FZH76lHnznAn2wOuD89Wvzbbg3OKM/dO/S5fInyvkl+VV/5aDcWAWKaUwL0f5E+vnnazkEKpuNiwj0yXauLds0wQh0MFh5a96Lip48uj6oI9AJ/R0VXasQrUDZXyRWIjnSwUqkuf/f9Vagua72/BZovk8+T6DpaP2d1qaEdi/Qp96jP49+dcli0AJCoFXZc2p+pjELNMVSTnewlHN+ouqhcwU6c+bsKfmodg00HzhXoHSKqd+1omZCESjzYb32YU2B7g7WaqXPgECNwRCoPQ0EOleg5B7/ye6LkSU6x+lamo0UjdmAvRI4V6CkD/9+3rZNEo5AyU3eBH14g3Trn72dzpw3GZzeFz31e6+SjvhJer10j/X7L8su/MMbA/Eqkuj0xz8lOU69Ofs9rAM/eOq9yWBtsjo49ZbyApLi6N3BYOX1NP2IvO6s2lKFQI3BEKg9DQQ6X6CHQzofNP2EzUsiJtz4CbtDBUjv8VmhYurnLLAg0O+kucsBo/UX+dPNE5BAhS8n4qroZWq9M9kT3JPviuulp/c1gYpXrVxmOU9d4mFr2e+ZCfTLq/Sn8gLSu7/O7r3+rsyeP1wI1BQMgdrTQKDzBZotMLpA7zzh64vOfYu1IPmqpeSVHWUlEg3UFimN2JKkTKBTz7s9zXtzLf2ePCaBMhU+vkhbgEe36BXRxxfZk48vktvsyQlrJdLW4mV1EOnB6uD07fSzG+w6Kh2Yen4/fXh9MMud6XlAA3+jvoC4+Kn/RPOx9HvaxVgI1BgMgdrTQKAWgfIl7mxRO+H4gxeT5GW+Fj5N77+RJC9clYPzuUBNoMc3qTIzgfJppK0QkkAnvGHJW53s5y5T5Oxx0acnqltTBborWo27wqZrPHfehFKg/DHlBUKZ4nX6tVUI1BgMgdrTQKAuO9KPFjLgk+22evDBCfToupDeg1ViON6HZxrNvew1ywAAIABJREFUz1YqCDRzHnOtFCdruWZIgbLfp75gj9tUxmvDTVELNN7kSyLQ6on8ZFkKgbY2Bh+aQM/QHryEPMH68LwjLwV69Kuffe+ZgSbQTJUsncxZLlDFlTxW5BZXDCDQIJJDoFoiP1mWQaCPWtwXNCSB7hUEmu7Kq5/i34+eGWTDQ4pARRZ2o5JA8y+AQANMDoFqifxk6b9AR74LhswlJIFScanSI75by1/qnAwGK89+/fu/1rvwaIH2LzkEqiXykyVugVYpvjlO6LZ3bRGQQNmlS20E5/HF0/+FR4hLnWv0Ues1UKtA9WugEGhwySFQLZGfLJEItBxefHPcYgPTSjgCFSuR5PC4MN3uU//E7ZbvqU9WDaPwPEcFgaovgEADTA6Baon8ZIlZoGLBEQSau52thb93iY+P8wmadEXQGn18IjcZERdIz+ynR3SV0RqT3zfS8nmgdoFq80BjFah1u6Vgj9xD9igEWn9DLAMQqLYcPgy6F6i+G5NciXSW3SPO5Mbb401FvlLolmisDrIlSupKJLtAtZVIkQrUvmFdqEfuI3sMAnXZUrAcCBQCFZQK9Nk35fpJthY+W8cubTYbhT/5utDg0Q26P51cC08XyT8n1sJXEGj+BbEKtMKWyZhI74qXNPYztIQT6R/dTJLkpbfzd1ilTdI1P76TJOtX+WJ4MRI0K8Upa8eJ4h/zg7Vf0xhdCzQCghVolaIdEKgrPtJUOEPLJ1BReFOUfuN31vm1za/ssHtX7/DSnAepUopTE+j8YPXXNAcEaqW9onL1y4q50db7aZjuisrh3NRBKyo3Ss6z4pp0tSXfYenzmwmvGpec+wntp7N25ViW6ZyV4swPIlmD87+mQSBQKxBooECgcaAKVG7/wWQ4yjYFPS8tKAtu8gClFKcq0PnByq9pEAjUCrrwxmB04edT4QwtXReebvL59uw21xvbmmmsFvmgmzappThVgc4Pzv+aJoFArQQrUAwiafervazqr/eRxOP/cH0RKN/k84VvKwWR2O50ogEpt1IasR0+85XkVIFagnO/pkkgUCvhCrTCJBkI1JWWpjEtn0DT+3zT5JcPZtvOsRt+BZr7NU0CgVoJWKD2adoQqCstTaRfQoGSrvu/vZEoOyCbW6D5fZWsAtU2YZK/pkl6KtAjtwKcpYQs0B4n74lAsZTT8H/EmNWBV6+BFpyojgFZBFo6YDRueBi+nwK9d6lOvU4LEGgnySFQLZGfLJ0LVBbjYD9HWW3jcieqpTgtAlWClV/TIL0UaM2CxxYg0E6SQ6BaIj9ZOhcosSAtrvmIOVObB1p0ol6zkxbfNAo0H6z8mgaBQK1AoJ0kh0C1RH6ydC7QbIkQM5+6EqnoRLVmJy++aRSoVrcz92uaAwK1AoF2khwC1RL5ydK9QPmC9XUxwegRHed5Wa6Fpz9UJyo1O3nxTbNAlWDl1zRGfAKdDE5/TDe04/uApOk9uinIydf22VNrk9XBqb/nFeNZWTqKtjlI7cOFQLtIDoFqifxkCUCgvSJKgX53thNd+q7YzYnKcjL4MjHrU//EBSoLfGpVQuofLgTaRXIIVEvkJwsE6pcYBToYnN1PH15nGzBPBiuvkz470ehl9tTp2+lvZnvVr/EXnF5oUhME2klyCFRL5CcLBOqXKAXKdu/khZF281WSJmJTZiFQ0YdfsAcft0Axkd6VlgS6lBPpe0SMApVb1+dallKgoj4IFyjvwy/ag4dAzcEQqD0NBAqBembha6Dcm1k5pV/97HvPDLhA+VNyFH4v/6AzEKgxGAK1p4FAIVDPeBUoLfLBWCsK9PFFcn/RHjwEag6GQO1pIFBngRYWtwdI7AKlVTuf/fr3f329TKDp7spbC/fgIVBzMARqTwOBQqCeWVSgopI81SW/9jm7BqoJlE4M5UNOCxCzQK27NS2SHAKtkqauQE2nDAINkhgFmnOmLKQ5WS0VKOnD31p4UVLEArXvF7pAcgi0UpqaAjWeMgg0SKIU6OD5/fThJWrLxxcHZ/bTI7oyaU0R6Dd48O7KM6K9usDhRivQCjvWuydPIdBKaeoJ1HzKeiPQabI1HSYbRI3338g2jZ89mKtMzATKinlQRk0X2HQiRoGe5ONG7NrmnliHdIv21LPLo7uDgZxEv3APPl6BVqmZ5JycBUOg9jS18sw5ZT0S6NeGbI+PO2L7eCrI7MF8ZWImUFnpKNDmaIwCPf3xu0Sfr3FX0lH4k69zd2YCPbohxElaqAtvK9JeVU7P9LrU46ddVuWsSfWanC50/e6saGWNpwndaO4P5CctSHx8h8lSPqhUJubOHIsK8mKzz8CIUqDV53XKa6SLAIEGCgQax8ktCHRWSDNlm3xuzR5UyhhzgYo+fJg9+L4LdPExeHTh5wSjC29Pgy58oQuvbNEpBcoeVMsYc4HyxwLtwfdcoA8XngSaRixQDCItQicCXY5BpKwvfvy7f//hiwkXqCjzni+sKaQ5zgUER58FSoeSFm+ARixQTGNagG4EugTTmDIVfvKicKVFoE+2yXOB9uB7LdA9tu/dwkQsUEykd6cjgfZ/Iv00K/2WrL/0j//8+x1FoPmOurw3Wn8n1B58hAJtnZgFGnHyZRWoMZGfLMEIlF/7nF0DlQ/mKhNLa9JJog3XhnMGArUStUCxFt6VrpZyGhMtfCgsSzACldWMpsP8JU6ljLEUKOnDv19S8j0IIFArEKgxGAK1p4FATQJNzh+kxx8M89dA1TLGWb99tP5iw8U1nYFArUCgxmAI1J4GAjVcAx2LdUjv0955NrKUr0ycCXSahNqDh0DtQKDGYAjUngYCnTcK/8JVfn82SylXmTgTKGmtBtqDh0DtQKDGYAjUngYCXXxHenm9NEAgUCsQqDEYArWngUAXF2iwY/AQaAUgUGMwBGpPA4EuLNBHoU4CTTsSaGycAGGifZdBoCyki1ES7hASBFqJrr9/wID2XQaBspAuxgnd4S5U+lxxFAAAGgUCBQAARyBQAABwBAIFAABHIFAAAHAEAgUAAEcgUAAAcAQCBQAARyBQAABwBAIFAABHIFAAAHAEAgUAAEcgUAAAcAQCBQAAR7CdXQW63g0MGNC+yyBQOpBMW2BHeivYkd4YjB3p7WmwIz0E6hkIVA2GQN2yQ6D1gUA9A4FagUCNwRCoPQ0ECoF6BgJVgyFQt+wQaH0gUM9AoFYgUGMwBGpPA4FCoJ6BQNVgCNQtOwRanwAEejg89+Hs3rhYcVMNCBwI1AoEagyGQO1pIFAI1DMQqBrcsUC/RHBLDoFWSGMXqHICGj6e4ARaAgRqAQJVg7tN/qUv5f+AwznyJRGofgLMiVo6nKqJqodCoJ6BQNXgTpN/6UvKH3A4R74sAtVOQMPHE4hAP3kxSTbepvdEF/7zO8MkuXAwSq7pAYEDgVrptUC/9CX1DzicI18SgeonoOHjCUOg30oYRJZCoIdD9sDGt4RAcwGBA4FaefrpT+PiS43T9TvkFATa9QHl6fuHX4MTYksJcZqoLF85SB/tJJsHQqDHO8nG3fT4fe5MNSBwIFArEGigf8MQaBwUBbrFf66/IwQ6TfhVz7EUaC4gcCBQK+jCuyYvxNeLRhfe//EE0YXnXnyynQl0xI1JHuICzQcEDgRqpdcCxSCS8dd7SoNBJMMo/EygpAcvrnZmg0izgMAJWqCPLw4Ez77p9QgeX1x5q3JwvwWKaUymX+8pDaYxVRCoNCUEWgUHgQ4GZ3wewfIIFBPpXcFE+vmJqoeiBeqZGgJ96j124+iXq4M1j0cAgXpJDoFWSGMXaMVECx8KyxKiQLNroNykEKiF+gJN073B6X1/RwCBekkOgVZIA4HaBSpH4acJBFoBF4E+WGU3H95YHQyevU0fmQzWJquDU2+Rx3IXSfmd2/wlpz/+KQk/JZ669yp56uRr+ykE6ik5BFohDQRqF6iYB/rbIQRaBXeBEmMyLqdUoF8m955674F4bI2GiYCVy+wlpy7lnnpXXEylLVkI1EtyCLRCGgjULlC5EmnzBxBoBZy78I8vDs7up0e3BlR/E+LC2+lv0t3BGfYYDSUyJY99doMFULM+v58+vM6emgxWXk/To3eZfSFQL8kh0AppINAKAmVr4ddza+FnAYETh0A/u8W8tyfG4tnPCbOkdOHRdRqwK66U7tKAB2Lg6cEqjdjld0jcGgTqKTkEWiENBFr9Ozgbjo+GwAU6m8Z0lspPaO/BKvHkhDUsqRHlRU5h0ZTKlQRwcWq2hEA9JodAK6SBQO1vUe6qHNVGdpw4BHryuX9NFZ8Sd05Ea3MyKI4NsSumYtxp9ujRr372vWcGyyXQeJMviUCrJ/KTJUiBTtnuIen9YXF7+tAJXKDZNVB+t0yg6T0+VPTc/iye3dAE+tEzg2xICQINPzkEqiXykyVIgZKuOyeC7Zc04hJoXnuT2czQo395la1VmtcCJQ3VlWe//v1fL1kXPt7kEKiWyE+WIAVKGp9vEH1+9Wp0/oxKoNklTsZEnVq/R1ql+jXQnED5tc/luwYab3IIVEvkJ0ugAl2M4+7EG5NAs0F25kchUKlJ9lMEEEueSVWBylSTVQg0juQQqJbIT5aYBDqqOCZ//0p3Y/dRCZRP80w/YhKcZLKkjz0UzlTmgSoCZdNF6cqkNQg0huQQqJbIT5YeCrTTyU9RCTRbiXQ2nXXh5UokFqquRMpfA90T65BuUdFCoJbkFTcIgkDtaTwaq9pZmZ8FAvVLXALla+H5vM/sGih7bOU1cYcOJz0n1sIXRuFPvs5fBoHOT151i0oI1J7Gn7EqnpX5WSBQvwQt0DCIWqBOE+krb5IOgdrTWPJUn0hf9awsdDjVE1UP1d7iODl/fCdJ1q+m6SesljF79NHNJEleustD8kWO6VND+dQ02ZoOk413xLD9C99mZelkAc9cYGtAoFaWTqDVy/RAoPY0vgRa+awsdDjVE1UPLQj0K3za59U7s7mfU76byDozplLkWD7FbydfI/fOfZjemU0czQSaD2wNCNRKdFU585xgpSrrl350oIP3pp6ooKpyVqN356QMrSonEd65n7C587QROk7ojiFEmZt3089vsjtPtvNFjsk90kgl9+hT04TG/YH8pK+lDdlrWRdeCWwNCNQKBBroHysEGt45KaMgUGY4UbyY228k1iCN+PbK/A7fXlmukxc7L3M7ii3syYu3MoEqga0BgVpBF94YjC68PQ268IUuPPOj3KyOujAbBmLuVIocZwXnDofkKbl1vSAvUDWwNSBQK0snUAwisTye0mAQqTiIRH882eYupLrMdv6k2zGpJeaIRSUkfjpbLX/8u3//4YvJTKBqYGtAoFaWT6CYxpQGKNC+TGMqFahwHr2hFjk2CPSTF8WDEGjwLKFAMZE+RIH2ZCJ93RZofkwod3l0/aV//Off7+QF2sn+9b0S6JHHwp0zohZovMmXRKDVE/nJEqRAy6+BskfVWfJCoPzap34NtJPp9HEJdFfU9KBMcrc59y5dThsAAu0kOQSqJfKTJUiBylF4IsFCkeNR1uhkg0hiAEpEDHOj8Epga8QlUFEHibGrr8ZUd7vzBwTaSXIIVEvkJ0uYAlXmgepFjulTdNHSVjoTaHL+ID3+YCivgX4n1QJbIy6Byl09U7rC/fR+4UkItD/JIVAtkZ8sYQpUXYn0aDtX5DhbYHQhnbUux2Id0vss14gPJuUDWyMugfLqxoxJplIJBNqr5BColshPlkAFmj6ia9tfFuvYj4tr4TfepjeVUfgXror7xzcTljMX2BqRCfTxRSlJ0YN/eGMwGDxLd1/i+9VdTsX2TOwx+fybhnTVDhcC7SI5BKol8pOle4H2i8gEmg0jiR58bv/PTKBy01C+J2hWSM79cCHQLpJDoFoiP1kgUL/EJlC5yedE+nG2A73owpNG6tn99OgWe2yX7UN/a6DvK1rrcCHQLpJDoFoiP1kgUL/EJlA5jLTLlCiLJLF2qRDonmij7s3KdC52dTRqgTpOpK8YDIHa01jy1JlI7wEI1DOxCVRsRP/4IrWkWoWT3zu6npU2Pr1PHjq10PVPdrgQqCkYArWngUAhUM8sJFBZ5f1ymmp14LlASQ9eQh6b0J8nX1tohRIEagyGQO1pIFAI1DOLLeVk3fVd1nXPaiaxG2UCTe9dYjefW0ChEKgxGAK1p4FAtbfY0aL1hohPoLS1+fjiGr1Z3gLVVigd/QutM6cv+6wBBGoMhkDtaSBQCNQziwmUenLCJVl+DbRkwGhvkWH4mAVae/+eYI48SoGWfNwQKATqmwV3Y5oM/uq7Yj2SGIUn0pyNwsuReSpVOelJ/nQ73HgFWn8HyVCOvEr24ARa9nFDoBCobxYUKL3KucZv6vNAv5E9ln60SoLIQ/T2w+vL2YV32MM8kCOvlD00gZZ+3BCoSaBZIWO5EZ3YTqnd3ZQWJUKB5jvkuZVItO3JzCpXIp1NZyuRlnIivUsVnTCOvFr2wARa/nFjIr1BoLntQ8ayvBx7YtzqbkqLEqNAH6zO2pMP6QjRc3zd+9ENPljE1sKL+Z/s9spC85iircoZWHFG77RVlbN6Ecx6NHS4waFV5eQCzW9gx8vAHQ4TpThcHMQo0JaBQAMFAo2DUoHmCxnzjZmmyT/wrUFj6sFDoHbQhTcGowufo/zjRhe+tAuvF/GgW8+v/5hXLm6zrPvCQKBWohUoBpEWoaVBpAaPpzRLIAJVysgxaR7vbP6RtkRHnZQ2cgYCtRKvQDGNaQFamsZUmb4JNFfImPyzeXA4PE8aoe9kT0QCBGolYoFiIr07LU2kr0zfBJpvgVJzTknLc5xsRdaDh0DtxCzQiJPHKNCyNBCo/RooMec14lDalR/H1YOHQO1ELVCshXelJYEu60R6pZAxaYf+DenFk6c2rkQ1iQkCrQAEagyGQO1pINBSgSqFjKlHqUjpj6gmMUGgFYBAjcEQqD0NBGpdiZSyOsX0xiiJahlSCoFWAAI1BkOg9jQQqGktfL6Q8ZS3RMWPiIBArUCgxmAI1J4GAsWO9J6BQNVgCNQtOwRaHwjUMxCoFQjUGAyB2tNAoBCoZ56OjRMgTLTvMgiUDiTTFhBoBbr+/gED2ncZBEoHkmmLPr83AABoFAgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEezGVIGuN7MBBrTvMgiUDiTTFthQ2Qo2VDYGY0NlexpsqAyBegYCVYOR3C17LwRaPZGfLBCoXyBQKxBoJ8khUC2RnywQqF8gUCsQaCfJIVAtkZ8sEKhfIFArEGgnySFQLZGfLBCoXyBQKxBoJ8khUC2RnywQqF8gUCsQaCfJIVAtkZ8s3Qv0cHjuw8V+9zTZPFgsgz8gUCsQaCfJIVAtkZ8sEKhfIFArvRXoFwiNJS+Nrxe9vAJd+MwYgUA9A4FaiVqgc64/feELJX+n4Rz5kgi07AQtfmacD6d6ouqhEKhnIFA1uBuBfuELZX+n4Rz58grUw5lxPpzqiaqHlgr0cLj5pw+GSbLxNn/0/pUkeeHq7Pk0fbK9/k6ajpPzx3eSZJ089QkJv0DNSQT6pzvDZP3lu/y1j26SZ166y19sSEue4NIdJVuu77n0zflMVhEIVA3uRKBf+ELp32k4R760AvVxZpwPp3qi6qEGgW4Qt1GYz8az27pAv7LDnrp6h/2gGpwm4rXr12jgdMhffC2dk/Z4h2aTWf0BgVp5+ulP4+ILTdD1myqhINCuD6gGPTwdRk6IPXnEaZICTZJXDtJHO4m498rB8fvitirQ5NxPiP54I3Sc0MemCX/tFRb/ZJu2S8mL6VPmtGOuVN/dfwjUCgQa6F8sBBoHJoFu8Xuio57SViJtReoCZS1GEc4jpqJ9Se5tydeKn/PSMnN67sFDoHbQhTceCbrw9jTowhu68LkuNVec8vxMoMx7sufN/DdNxDAUbU7Kvjk3pDktj/Pdg4dA7fRToBhEsv16T2kwiGQQaE6TitYKg0j8Dn9QCPT8LJT04CUkxJyW9+G9D+BDoFZ6KlBMY7L8ek9pMI0pEIE+2Sbu9N2DD0mgD1afem+xxJPB6f3FMpQRtUAxkd4VTKSfn6h6aNMCzVtyjkDT0fo73nvwEKid3go07OTLLNDSRH6yBCnQuddAywSqXAPNvXZOWhq9lanXGxCoFQi0k+QQqJbIT5YgBUq8yMQmBtJ5K5GPv5cLlIuRj8KPxGVNdnnTnJb14d9XjOoDCNQKBNpJcghUS+QnS5gCZRM20/tD6jeixY27dF7nPIGufyebB0peu3mXrVPampeWvnj9xUVXkRbfnOd8VZgr0Aerpz/+6epgcOpN/ui9S4PByddnz6fp44srb6Xp3uDM0buDwQp56iMSfpaakwj043dXByvP3eavfXiDPPPsbf5iQ1ryBJfu7mDNcLgQaBfJIVAtkZ8sYQpULhlispzy26/smAUqVyKxpqpciXQhnZuWJfbdgw9RoKeI2yhr9MG92W1doH91nT31+rvsB9XgZCBeu3KZBk5W+Ysvp3PSHl2n2WTW0sOFQLtIDoFqifxkCVSgubXw5PYb9PbxHIHytfAXxIwkthaer36fl5auWfLdgw9RoIPB8/vpw+sDce/5/aNb4rYq0MFT/4nojzdC9wb0scmAv/YSi398kbZLyYvpU+a0e1yp5u4/BNpJcghUS+QnS/cC7Q5pYZ+EKNA1fk901FPaSqStSF2grMUownnERLQvyb01+Vrxc15aZk5jDx4C7SY5BKol8pNlmQXqfww+SIHmutRcccrzM4Ey78meN/PfZCCGoWhzUvbNuSHNaXmcuQcft0DrfnnDOfIlEWjlEwSBLsoj75NA0yAFmtOkorXCIBK/wx8UAj0zCyU9eAkJMaflffg5A/gQqDEYArWngUDDEOgoaWAICQJlDxF3mnvwEKg5GAK1p4FAwxDoWOzG7Jk+CzRvyTkCTXdX3prTg4dAzcEQqD0NBBqGQBsibIHOvQZaJlDlGmjutXPS0ui1TL1lhwuBmoIhUHsaCLQwjSnb0MO8ND2awklhC5R4kYlNDKTzViIffy8XKBcjH4XfFZc12eVNc1rWh7+lGFU7XAjUFAyB2tNAoEWBSm1CoE7UECibsJneW6V+I1o8dZvO65wn0JVvZPNAyWtP32brlNbmpaUvXnlmzirSmAVatq2Pt+QQaJU0Io/pTCylQKXbIFAnaghULhlispzw289fNwtUrkRiTVW5EulsOjctS2zuwccs0NKNJX0lh0ArpeF5jGdiOQUqOvEQqBN1BJpbC09uv0pvH80RKF8Lf1bMSGJr4fnq93lp6Zolcw8+YoGWb23uKXkKgVZKw/I4nIlmjicIgZ77UaKWyHx0M5F1iWdBcdQ+Dkig3SEtXE60AjUU1/GTnAVDoPY0NI/LmWjmeMIQ6H/eUSodid1A1gv7ekZQ+xgCTXPTn0qJriqnJM4ajtUJqypn9YqaJjo9/AYpqcopRuKzTec276af30xy1oqm9jEESnr6cyaBphBosECgcVBW1phLTm57zHU1yq0Uiqb2MQS6O5g7hIQu/JxgdOHtadCFL9vO7ph14tXCG/l2XzS1jyHQPbEbs5FoBYpBpEXAINL8RNVDDfuBEsuppd/yI+/R1D6GQK3EK1BMY1qAlqYxVU/k83A8JKoeWipQ1u0WBhPezG/XGU3tYwjUSsQCxUR6d1qaSF89kYeDCUmgtBP/x/ZaoE3VPoZArcQsUCzldAZLOecnqh5aLlDaif9b6zXQ4GsfQ6BWIFBjMARqTwOBGgTK5l/mRuGJyYqj8MHXPoZArUCgxmAI1J4GAjUJlM3btMwDDb72MQRqBQI1BkOg9jQQqEmg2b5Mc1YiBV/7GAK1AoEagyFQexoI1ChQOQE+ffQGEdjLZWvhg699DIFagUCNwRCoPQ0EGteO9DVrH0OgViBQYzAEak8DgcYl0Jq1jzsRaGycAGGifZdBoHQgGVfq1j6GQCvQ9fcPGNC+yyBQOpCMG/VrH8fz3gAAoFHq1z6GQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBFsZ1eBrncDAwa07zIIlA4k0xbYkd4KdqQ3BmNHensa7EgPgXoGAlWDIVC37BBofSBQz0CgViBQYzAEak8DgUKgnoFA1WAI1C07BFofCNQzEKgVCNQYDIHa00CgEKhnIFA1GAJ1yw6B1icugR7Xq0/UBRCoFQjUGAyB2tNAoIa3OC7Wvzwcnvswd/f+lWvz8pYkaB8I1AoEagyGQO1pIFBXgR7vJBBoGRCoGqxH/5zQWHJbfDDJwxOo5bwY0nRgrHlZwhFoCfUEGgQQqJW2Bfrzn8//Sw3HccslUNt5MaSBQCFQz0CgarAa/fOfW/5Sw3HcUgnUel4MaSBQ7TxNk63pMNl4R/TAP78zTJILByMqSyrQT15Mko23U9pDp0iFSpuOks0DlmTzgCU4HG7+6YOheImWrg0gUCvtCvTnP7f9pYbjuGUSqP28GNJAoAWBfo047tyHXKCHQ+bJjW8JgX4rkd5UBUrubqXMo+vviHtCoBtX+Evo02q6NoBArTz99KeL8fM2WPAYY6QgUMc8OB3NckLsySNO0zRJNu+mf+D+I0LcuJsev89VSfX3ykH6aIc1M9UuPGlqHvCIa/QpolEhUPkS2vtX07UBBGoFAg0UCDQOCgJlbUjuv2nCr3qOpUBFO5KGqAJ9sk0jp8k/0BBmUynQ3EvUdG0AgVpBF76T5OjCzz0e1ywhdOGl5M7TS5pMf0SPXKDcrU+2iwJN2WXN0fqPqTun9LVCoPmXqOnaICKBHu17+v01E2EQqZPkgQkUg0haouqhBYGyYSDmv5kjs0EkeqdUoFMWv/m7pBmzAAAXuUlEQVRH2hId8Yuk57WXaOnaIEiBPlh96r3Cg/cuXba97vHFgeDZN81RFRIpRD2NCRPpXWlpGtPyTaRXBcrbj3MEOpWjSk+2Nw8Oh+dJI/Qd3p0vE6iSrg2iEejR9UENgQ4GZ0xBVRIpRD2RHgJ1paWJ9MsuUGsLNBMoNeeU/BwnW6wHjxaoEXeBitcd/XJ1sGYICl+gPpNDoK74SgOBzhFodtGSq29uF5684BpxKO3Kj9kTRYFq6dqgnwJN073BacOVTgjUW3IItEIaCHSeQOWI0jSxC/Rw+DekF0+e3Lgi5oIWBKqma4OABfpg9fTHP10dDE7R65l7rF9+OZ0M1iarg1Nvpem9V8kDJ1/LazInUOHgXJB45d/zRCQ5f+WusamaHS4EagqGQO1pINB5AhUTN387LBfod/IvJPfFS3iGEoGq6dogaIGeusSvZ67lBfpl4lTy9LviWme+oVkQaD5IvPKfeKKj6ytv8Zfwn/MOFwI1BUOg9jQQ6DyByqVDmz8oCpR0yMX6IoGY3TkSj5YIVE3XBkELdDB4fj99eJ36Uva8J8SGt9PfkJ8rr5MH3x3k++N6F14Jkq8UifZ4y3Ni7OrPDhcCNQVDoPY0EOhcgbLF6+u5tfD0MWHD45uJsmOdmIKvzMTXXqKka4OwBbrG79FGYiZQ3mIUPW/y6NrsdZlAP7vFnKkEyVeKRKIPb+/BQ6DmYAjUngYCrfIWPY/6YBDpPSlO2cvOBKqML+kCnU1jOqsHyVeKRLwPX6EHH7dA402+JAKtnshPlsAEKjdF1vaid8VzugoELVBuPE2gWZf76Fc/+94zg1KBnnzuXwtB8pVyFH4v/+Dcw4VAu0gOgWqJ/GQJTKBTthVIen/oZ3d5z+kqEK1AP3pmIEeYJgMxwpS7BprqQQWBPr5I7lfowUOg3SSHQLVEfrIEJlA6pM6HfbzUj/OcrgKxCpRIc+XZr3//19fnCTQfVBBourvyVpUePATaTXIIVEvkJ0tgAiWtxTeI77561ZfwPKezEqlA5bVPwyASRw0qCJRODDWv+MwdLgTaRXIIVEvkJ0twAjUTQVHjaAUqVTlZnSNQNaggUNKHv1VlURIE2klyCFRL5CdLPAK1FDUOhJgE+o00J9DBmf30iC5UWpu9riDQfFBOoN/gz++uPFOy61PxcCHQLpJDoFoiP1miEWgUJeUiEmi6KwaMuAb3xBKjW/lOuH4NVAnKhp94opRdIq3Qg++LQKvtJRTOkUOgWiL+w2lLqFwWCNQv8Qj06Ab1nTIKf/J1dR5S6Si8DMoieSIWXmlbkagFmn15K+5mGc6RL4lAa06kd9uUtPrhVE9UPRQC9UwoJT0Kvi2nFwKtup96OEcOgWqJ6D+O2+JXP5zqiaqHFt7i/StJ8sJVfvvRzWGSvHSX3lQqFM9qcuYiZEVkD8fvi2UWaKUx+H4ItHJFn3COHALVEqXuhZmqH071RNVD9bc4zpUhng6z/ZLVCsWZQPMRsiKyp/fggyUW6MMqk0BTD1U5/VK/QuTCdP2WDfiqytkpJ070/uxpVTkPh8krB8fvMw8+2U4uHNAyxHQnkEKFYupMJUJWRA6IpRXo7ryyHwoQaNdv2QAEGsfZ0wTK16tzP8q16yUVioVAlQi5D1NALK1A9waDs9Wqc6ILbwxGF96eBl149S3mB4eyInCszntZUWM1YhpW952ytAKtTh8EikGk2oQo0D4MIsmNO/ntRELMWFbQQ42YtrfGvSoQqJVeCBTTmOoSpEB7MI0JAl0YCFQNxkR6t+y9EGj1RPzHYv4MTqD5a5rlAs1HQKCMZgV6VO3KZnV6ItDYkkOgWiI/WToXqHoNND9ZvkygagQEyqgn0Nk288++OTdwj42q37t0ObvtBwi0k+QQqJbIT5bOBZqO+Li6KAvPjcjMWFrUWImAQBmuArXMO2LSzErGQaCRJ4dAtUR+snQvUDYPlG4az6rI0Ymd6SdsAlNpUWMlAgJl1BWoWHB59MtV+/7x2WZ1/oBAO0kOgWqJ/GTpXqByJRJrh8p1RhdSU1HjfAQEynAUqKhVPB8ItC/JIVAtkZ8sAQi0uBaerX43FTXORUCgDGeBiv2ZHt6gF0Rvs4f4bXZxlHbb90RxD9GFz0U+WD39Md0Z9NT8C6llhwuBdpEcAtUS+ckSgkD7RIQCnawyS67w6u5Z0bgSgaqRpy7NYmsdLgTaRXIIVEvkJwsE6peoBMq68MSZp2+nn90Y0K1Adtme87dYyffCIJISSVX7/H768Pqg0h52+cONWaB1v7zhHPmSCLTmRPpFgUA9E5FAP7tF25bEmfxCKHFnttcys2ZBoPlIKtA1eufBarU9mHKHC4GagiFQexoIFAL1jPs0prNKUc3T++TO7JqmLlAlMhNnpUrG6uFCoKZgCNSeBgKt8R2MohCnQkQCPfncv6Y5AbILoqwk/MnXRJkkVaBqpFYgpM7hQqCmYAjUngYC1d6iujpT8NthknzlwFKIU25tFxIxCLS0VrG4cY+PDD23XybQfCQE6j85BFohDQRaQaBTNjHUVgYJAuUsKNB8u5Jw9C+v8jVKaIEWqb31RDBHDoFKxDnstUDHpPkZTR05hegEql7ZFOzRoXXbNdAlFGj9zc9COfIq2ZdDoPIc9lqgI7YXPQRajYUEKsfWiR7PZFZkP02j8CxyKQXqsP1uIEdeKftSCDQ7h70T6Kza5pTv9/mjrHgcRdpU7CZCFyGJwh+52p2Ez++QOxcORh25Nz6B5md3EjeS23RyZ64L/420fB7o0gnUpQBEGEdeLXsvBGohV9oohMPJJaoeWi7QXLXNUoGSbr1olbJwek8INFe7k1eiI2x8CwI1UKjeXrYSKZtIz4rFrZWuRHIXaNdVuRwJqK5YI0RaVK56OTh3un6PClpROS5QpdpmaReeVUFigpS1kWTpObV258ZdmiaBQA0UBJo+pKNGz8m18ESSK2weE5fm0Y0BW9J5RouEQHsHBBqxQJVqm6UCfbJNDTlN/oFvdUdsWlK7U5aZG0OgwYIuvDEYXXh7GnThy7rwarXN8kEkdllztP5jXo/zfFb8OF+7k7+QNWgh0ECJVqAYRFqEMATa10EktVhcuUCpNI93Nv9IW6KjrIq8sund7BUYRAqWeAWKaUwLEIhAezqNaY5Ap3Jw6cn25sHh8DxphL7Du/NlApVToiDQYIlYoJhI704oAu3nRHptMmipQKk5p+TnONliPXi0QAUQqBqM5G7Zl0SgMpGfLIEItHC5s2wi/Ti5RhxKu/Jj9kRRoNk10M7m4EOgVqIWKNbCuxLIRPpZooUPhWUJRKBqtU2DQA+Hf0N68eQFG1fEXNCCQOUo/BSj8MECgRqDIVB7Ggi0VKBKtc2ZQL+TjyT3qTLpD2bbEoGKeaC/HUKgwQKBGoMhUHsaCHT+SqQL9DHREx/J9UUCMbtzJB4tEahcibT5Awg0VCBQYzAEak8Dgc5bCy9WtAuBykKckilfpyR+lAqUrYVfx1r4gIFAjcEQqD0NBNpGSQ8MIoULBGoMhkDtaSDQJgUqV4TKdmnrQKBWIFBjMARqTwOBNinQKdtZJL0/7Gqz+k4EGhsnQJho32UQKM25hI7Q81GkjsrRQaAV6Pr7Bwxo32UQKE3a5P4bRJ9fvdpVOc8+l2wGAIBGgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUABAMARbGdXga53AwMGtO8yCJQOJNMW2JHeCnakNwZjR3p7GuxID4F6BgJVg5HcLXsvBFo9kZ8sEKhfIFArEGgnySFQLZGfLBCoXyBQKxBoJ8khUC2RnywQqF9iFOiD1QHnr1/bt8U+vrjy1oK/DgLtJDkEqiXykwUC9UvUAh0MrHaEQGNNDoFqifxk6Vygo2T9HXl7nLsdKXEK9Kn36M+jX12yGhQCjTU5BKol8pOlc4E+2c5KEB8Ok2ueDqczYhYoUej1wZn5sRCo/shfCI0lt8TXi15Cgc45OX0RKNXmFrtxvJOc93Q03RG3QMlN6kf5gLTlvVdJ7/4ku0AKgWoP/OUvcw0azpEvo0DnnZzeCDTruI+Tcx96OpruiFyg6e5grSDQd8UF0tP7EKj+5f3LX+YbNJwjXxKB5t/E3JPTH4GSliftxM868I9uDpPkpbvidkJuv+3pKJsndoHu0T68KtDJYOV10rsnGr0MgWpf3r/8xWLQcI58+QQ6/+T0R6CiEz+SHfgp0SflGn+KseXpMBsndoFOaDtTFShrlLLro2ueBPppDPylAbp+T/MpCLTrA6pA709KCSfElhKzM0U771PZgX+ynVw4SI/fZx17YlV2O5rOfQ8FKoBA+/63CoHGQVGgpBP/N9uyAz8WLVH688k2uzxKno9leD5+gRa68Cmd4PSz7z0z8CZQdOENwejC29OgC18ykZ721EUH/nhHzAU9HG4eEHNuxHP9kxK7QEuugaYfPSNGkdYgUAwiuYJBpPmJqoeWrUSajcCTHryEPDSlP1/49oGfg2yB2AVaMgo/GQxWnv3693/trwvfI4FiGlPlX+8pTQ2BLsk0Jso0m02vCjS9f4XdfDkWhUYu0JJ5oPzap9droH0SKCbSV/31ntLUEehSTKRn5AWqLec8/rc3kiSaKfZxC1SsROIapf158vPxRf7sZBUCjTn5kgi0eiI/WYITaOmAUTxz7GMW6NG9SwN2i3j01O306NaAC3RwZj89+ukqroFGnRwC1RL5yRKcQNORuEkfOhxyccqf4ROnQPXdmCb83vPX6f09sQ7pFm2dQqCxJodAtUR+soQn0MNhsnk3TT+hs+vpIiVy+1E8q+SjFuizb8r9QOnq95OvH13PRuFPvs6niEKgsSaHQLVEfrKEJ9BsJdKFdLYSKZYGaJQCbRkItJPkEKiWyE+WAAXK18KL+Z/s9no885ggUCsQaCfJIVAtkZ8sgQi0N0CgViDQTpJDoFoiP1kgUL9AoFYg0E6SQ6BaIj9ZIFC/QKBWohZo3S9vOEe+JAKtfIIg0CCBQK1AoMZgCNSeBgKFQD0DgarBEKhbdgi0PhCoZyBQKxCoMRgCtaeBQE1F5UrWwccHBGoFAjUGQ6D2NBBoUaBSmxCoE1UE+qsbq4PBynO3KyfdpRWQ9pQqx+yhxYlZoPO3XlowOQRaJY2WRz8jSylQOYseAnXCLtCHlwazPZGrAYGWYNn8c7HkEGilNGqewhlZToGKTjwE6oRVoI8vDk7RZe4Pb1Q3aIktl16gtu3nF0qeQqCV0ih5imdkGQV67keiEy8FymsZ3/V0aK0SokCPrrOS7pS9wWzz+flAoAWsBZAWSc6CIVB7mnwelzPi93jCEOh/5pXhpUDFbiLrsRSSyxOiQCcza8rt5eluS4OTr1GtPlg9/THd7PPUmzzks3fJnbP7+S58/iHlteTOJbZTE0vDH9m1NXIjqcpZJOJCjpUItCpn9fqa5XR9/N7RqnLSvT7FSDwXKN/P7vObSYz9+RAFmlfaZ8xy74orotR5D1ZPXcpdHxV72536u5lAlYeU18q9Qteomvk+d/b97iDQQIFA46BEoOmY2ZILVO6oPIpmE9AcAQqUtDq1rvdksEIajUdEhZe5Hp/fTx9eZ+1UermUb0afCVR9SH/t8/vkGfrKPS7gSXa5wHi46MKbgtGFt6dBF77Yhf+Q7Zx8wAWa1fRQtriLhQAFWmwT7ubLxD1YlU1PXoKT+28yE6j6kPJa3kLlhhZ9eGsPPl6BYhBpEVoaRGr5eEIRKJ9OzwSaDcXHU8cjRxQCFUiB5vve0n+k2SkFqj6Uf63StuV9+Ao71scrUExjWoCWpjFVT9TE4SyQqHpoqUBZJ14IVHgzuxETsQj06Fc/+94zg0IR+JkSs0Ek7aH8a9XMrA9v78HHLFBMpHenpYn01RN5OJiQBEo78X9EC9SF2tdAWZUjOfqjCVQqMSdQ5aH8a1WBPr5I3GnvwUct0IiT91Sg7on8ZAlGoLQT/7e4BupCnVH4yeC5fXo1c+XZr3//19cdWqD512pt292Vt6rUnItaoFgL70pLAl3KifS8oTmmcz9no/DH8ZTizBGiQKUiKbtciWv09lFRoJlsuTaVa6DsIeW1Wtt2MlibKGs/DYcLgZqCIVB7GgjUJFBizATzQB2osRLpI1r5/fFFrszJalGgctK9Mgqfe0h97S73pZhvT/rwtyosVoJAjcEQqD0NBGoSaLYvE1Yi1cO6Fv7B6uDk67O18I8vDs7sp0d0+dGaLlAiWzrp85erM4EqD+mvpVNI760Kbe6uPFNhpSgEagyGQO1pIFCjQMV0+jR99Abx58tYC18R+25MD7LdmM7Su2L9EGkvntEFmj68yJ/77mwlkvZQ7rXynui3TwYVevAQqDkYArWngUCxI71nKuwHesQWsGf7gdKR9JOv8zlHmkDTo+Ja+PxDymtza+F5iirbjUCgxmAI1J4GAoVAPRPMjvTyAul8IFBjMARqTwOBQqCeeToU/qfBf18p7gQIE+27DAKlA8m0xTIL9D/8D//d/1gp8ESjDkVy5+zad7mFg6oNDucEBLr0PN3kVQck95q92YOqDQ6n30CgVYhXQ/Emh0CbILDDiR8ItArxaije5BBoEwR2OPEDgVYhXg3FmxwCbYLADid+INAqxKuheJNDoE0Q2OHEDwRahXg1FG9yCLQJAjuc+IFAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUBLeXSztEjLk+3z8wOck+cfe7LNamwlWekYX4nDPOp5R2b7wJs9qNo0+rXxfzgtfzq9BAItQ3yzCmVWR8n5+QGuyZXHDodu32tr4iCP2pidYvnAmz2o2jT6tWngcNr9dPoJBFrC8Q4tVP2I/HugPDxKxFfPEOCcXH1sKr/gnhMHedTG7Kn9A2/2oGrT6NemgcNp99PpKRBoCaLwKvkfPF+p+tGVRH71ygPck6uPjZItX0etPBbkURuzV/jAmz2o2jT6tWngcNr9dHoKBFrCWHzDxvkv2DRJLnySPVESsEBy5bHjHbcunjVxkEdtzF7hA2/2oGrT6NemgcNp99PpKRBoCSPxf/Y03/uZbryd9XlKAxZIrjz2ZPvcj0kzYaPul9uaOMijNmav8IE3e1C1afRr08DhtPvp9BQItMjxjvjqHQ61L7r46pkD3JKrj8lL+zWbKdbEQR61MTtn7gfe7EHVptGvTQOH0+6n01cg0CJPtkXXRlxFmiG+euYAt+TqY6SXtXk3/fxmzcFaa+Igj9qYnTP3A2/2oGrT6NemgcNp99PpKxBokY4FOhZdrmy2iafEQR61MTtnQYEuclC1iU6grX46fQUCLdKxQGe/rFZHr2OBOh71nEw820ICXeSgahOdQGf3W5lW1U8g0BlTfkXoWiMXs+YlL89X88+s42ugjkc9JxNlwWugixxUbaK7Bipp5dPpKxDoDOk482jpAsOpc5OX5qv7ve52FN71qM2Z+AMLjcIvdFC1aeJr0+ThSCDQBYBASzDO15tdPWpuRmXWcqj7Z9bpPFDnozZmF9kWmQe62EHVptGvjf/DafnT6SkQaAnGFSOzCSANrukZZd/ven9m3a5Ecj1qY3bG/A+82YOqTaNfmwYOp91Pp6dAoCWQr9RG6Zpl+dUzBjgmVx47HCYXDuiSu5odK2viII/amJ0x/wNv9qDaehedHU67n05PgUDLEFOM+TBmbpZHdvVICfCQXHlsnLgltyYO8qiN2SmWD7zZg2rrXXR2OO1+Ov0EAi0lv5Ni2VfP286aMrm6becb5Ft9oX4rxZ44xKM2Zk/tH3izB1WbRr82TRxOq59OL4FAAQDAEQgUAAAcgUABAMARCBQAAByBQAEAwBEIFAAAHIFAAQDAEQgUAAAcgUAB+G/t1LEAAAAAwCB/6znsLohgEijAJFCASaAAk0ABJoECTAIFmAQKMAkUYBIowCRQgEmgAJNAASaBAkwCBZgECjAJFGASKMAkUIBJoACTQAEmgQJMAgWYBAowCRRgEijAJFCASaAAk0ABJoECTAIFmAQKMAkUYBIowCRQgCnk5MQajlubnQAAAABJRU5ErkJggg==" class="img-fluid figure-img" width="672"></p>
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<div class="cell-output cell-output-stdout">
<pre><code>
[[5]]</code></pre>
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<figure class="figure">
<p><img 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GoGAg2HQQQaGk8BP8l9l4GnDCCZvoBAazD09w8sIfddBp4ygGT6IubfDQAAOgUCBQAASyBQAACwBAIFAABLIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAEAgUAAEsgUAAAsAQCBQAAS7CdXQ2G3g0MLCH3XQaeMoBk+gI70hvBjvQu68WO9GawI304QKBGIFCX9UKgZiDQcIBAjUCgLuuFQM1AoOEAgRqBQF3WC4GagUDDAQI1AoG6rBcCNQOBhgMEagQCdVkvBGoGAg0HCNRIpAJ1aLKBqo1WoA2j+h5Wv05HNxLJ6Y/I80c3yaNX7laVeDNJNr+9X/9k+gQCNQKBuqwXAnUe1fewlQJ9ss0ebr67tMSUPzzzUf2z6REI1EjnAv0ZwfbYFtVCoBUlZdE61wYCtenCH4ypNIkst+6mj8i/xRYmL3EwpiWO7pSV8AAI1EjXAv3Zz+wNCoGqz5sdXllSFK11bSBQC4ESc55PqR5ZL520Q68uKTER5pwUS/gABGqkY4H+7GctDAqBqs+bHV5Zkhetd20gUAuBTrkXp8lZ8fR8eQmiUS7OuSjpGRCokW4F+rOftTEoBKo+b3Z4ZUlWtOa1gUCbC1Q2OSeZHvM9dFHiyba4PXow9rIPD4EaeeaZPxb4mdcUzzdKCgItlBj6QkgG+HA84imxJ496rUTHPGtfFvWYLzHnQ/K+AYEagUA9BQINgxKBygao0r7M6TG7KzoRXfcJBCoJTqA1CoXXhcdE+qqSg3bh459IL+6AVghUliAtz+TcPh2Fh0AlEKhKG39CoNrzZodXlhx0ECl6gYoB9gqBZiXkPNDN/y2vWD+AQI1EOo0JAq0qOeg0pugFmulSuwc65zPmr2olCPcvJ8nLdzGIlAGB6ofa+xMC1Z43O7yy5KAT6aMX6DSbkqSOwqsCnRYmLWEaUwYEqh/a5lj7QyHQqpJNzhICbSrQidI/L58HOinMCy2+4gUQqBEI1GW9EKiZ2AWa3flcuhJJKSEUy9d1+gcEagQCdVkvBGomdoEqNziPbiRnStbCKyUOxsmVNL0/9rMHD4GagUBd1guBmoldoOqyI+LH/G5MuRJ3+K1RL4eQINAaRCpQLOWsKjmoQBtG9T1spUBL9gPNl/j0pSR58Yqf/oRAzUCgLuuFQJ1H9T0sdqR3DASqHwqB2lULgYYRFgJ1DASqHwqB2lULgYYRFgJ1DASqHwqB2lULgYYRFgJ1DASqHwqB2lULgYYRFgJ1DASqHwqB2lULgYYRFgJ1DASqHwqB2lULgYYRtiDQozvjJDnzDn9SOo1JL4G0xjoQqH7oMALFRPqqkoMKNPKJ9GLuPF/bXpLWOFcCaY3zQKD6oYMItMUWUK3qhUDNWAq01iUdXqBEmWfupkcfJEvTGmslkNa4AASqHzqEQNtsQtqmXgi0BnYCrXdJhxfoNMtTfH7JZiJaCaQ1LgCB6ocOINBW2+C3qBcCrYOVQGte0sEFmu2hzCjbzk4rgbTGRSBQ/dD+BdouEZN9vSkEWgcbgda9pIML9Mm2mpqjLK2xVgJpjYsEJ9BBcxo2zwE5NH19MuasnJ4z9IUy4ubX1LNyUhHSJB1sjL00rXF5CaQ1zoBAmzD0H1Fz+vpkINCucfNr6gIlbc2b2Rh7aVI5rQTSGhcJTqA1CqELX/dIdOGNRN2Fp5mPRJ7iq8sEqpRAWuMiEKh+KAaR7KqNVqANo4Y1iDQX0ztZ03KZQBclkNa4CASqH4ppTHbVQqBa2HqX1AOBKs4sTWuslUiR1rgABKofion0dtVCoHrYWpd0cIFmbU32oCytsV5CgmlMGRCofuggAsVa+MqSIQrU17D5aUzqzKWyeaB6CQnSGmdAoPqhEKhdtRBoGGFz12kxrH52yUokrQTSGheAQPVDIVC7aiHQMMLmrtPBmG6+dHRHroUvpjXWSiCtcQEIVD8UArWrFgINI2z+Os3FXkuszVma1lgrgbTGeSBQ/VAI1K5aCDSMsIWNEx/dHNNxdfmkZD9QrQTSGueAQPVDhxEo9gOtKjmoQCPfDzQqIFAjEKjLeiFQMxBoOECgRiBQl/VCoGYg0HCAQI1AoC7rhUDNQKDhAIEagUBd1guBmoFAwyFkgT5YH204ClUFBOqyXgjUTOQCFXnkxO5KZaPwuRLIyqnjSqC7o9HT7zuKVQEE6rJeCNRM5AKVOTflGqTlWTlZCWTlzONIoI8vrD07uuQmVhUxC9R2SxEItMuwLgS67Mp6IFB1W5DSrJxaCWTlLOBIoLPRid3RSTexqohUoItdeHutFwJ1HrUs7NIr64FA1W1BStfCayWQlbOAI4HujDYerGd9+M/eWx+NTu3t8Dbpw+vk2XO3ndQTr0Dtt1WGQDsP28p0y6/s8AI9uqH018t2Y9JKICtnETcCJT34tw+vyWGkB0SYhON/wwQ648/cdPCjFWiLxB4QaOdh25iu4soOL9An26d/SFPGMUeWZeXUSiArZxE3AiU9+D3+D4GY9Pjt9PAWl+bjC6QtSp+tve2gooGTylGapwPzga4/leCTygmGvk7NaP776UnlshEi2uYszcpZXgJZOTOcCJQo8xJvhtJnMzEev8sEKm+NurlFCoFa0vWnAoEOQfPfLyfQeUJHhT6/SUfeS3MiaSWQlbOIE4GK25873JE7oitP2p6XiFtFy/PBOm+ftgNdeJf1ogvvPGpgXfhpNiq0JKmcVgJZOYs4EahoXfKmJ2+OUuggErGoxMU80WgFikGk5SXDFqjXg0gSetuzXKBqCWTlLOJCoESZkkvpos0JgTaq1tafEGj3YeOdxiRYmpVTK5EiK2cBFwIVo+4U0k3Pt0CdDB5JIhUoJtJXlcRE+l4EWpqVUy8hwTSmDBcC3ZHjQzM21C7vgTKTLnTqhJgF2n+9EKiZqJdyKsPqS7Jy6iUkyMqZ4UCgbLBIPtpYjMLPWI9+R0xukpOc2gGBuqwXAjUTtUDlsDrR5PnqrJy8BLJyFnAg0Nni7uaO6MPTeaA/X2cCJf37E7fT9GM3uzVBoC7rhUDNxC3QgzEdVn90mY2qL8vKuSiBrJwFHAh0ZzHDcyadye6HfldbiXSqfU0QqNt6IVAzcQtUbq/EW5SlWTm1EsjKmae9QIkus7ucpPFJZUrXwq/pa+GPv9W6IgoE6rJeCNRM5ALlG3yeE0Isz8qplkBWzhwd7kjvePyIAYG6rBcCNRO7QGMiEoHKRZvK9kzOgEBd1guBmoFAwyESgc5Goxf20vTeegcbhEYqUIcmG6jaaAXaMKrvYSFQx3Qg0Gxhkot5SzkgUJf1QqDOo/oeFgJ1TCf3QO+9RvT5l2+49ycE6rReCNR5VN/DQqCOQVpj/VAI1K5aCDSMsBCoYyBQ/VAI1K5aCDSMsKUCzfYGKZ3GpJdAWmMdCFQ/FAK1qxYCDSNsmUCP5Nqj0rTGWgmkNc4DgeqH1j62uMMOBKo+b3Z4ZUkXAi25XH6brqOwZQKdiqVF5WmN1RJIa1wAAtUPrXtsyR6PEKj6vNnhlSUdCLTscvltuo7ClgiULuAUeixLa6yWQFrjAhCofmjNY8t2GW9RLSbSV5VsL9DSy1UvbPQT6Z9sb/6Q3+EsTWuslkBa4yIQqH5ovWNL89xAoOrzZodXlmwt0PLLBYEyJsl5MURUmtZYLYG0xkWCE2jkyRbtfr3h6Swr59AXpIir32wQclk5uS0P9PZlTo8lJZDWOAMC9Qu3fy79AYGGQV6grFFZaF+qelRKIK1xkeAEWqMQuvB1j0QX3kjkXfgJ34q+QqBKCaQ1LgKB6odiEMmuWq8FikGkjEJeeNqkrBKoWgJpjYtAoPqhw0xjgkCrSg46jSlqgQpVltwDlVk5tRIp0hoXgED1Q4eZSA+BVpUcdCJ91AIVC4tElo6ytMZ6CQmmMWVAoPqhbY4dploItPuwqyHQsnmg5QJFWuMMCFQ/FAK1qxYCDSNs1WYiS1ciZSWQ1rgABKofCoHaVQuBhhG2SqClaY21EkhrXAAC1Q+FQO2qhUDDCFu5nV1pWmOtBNIa54FA9UMhULtqIdAwwrbdDxRpjXNAoPqhEKhdtRBoGGGxI71jIFD9UAjUrloINIywEKhjIFD9UAjUrloINIywEKhjIFD90GEEion0VSUHFWjUE+kjAwI1AoG6rBcCNQOBhgMEagQCdVkvBGoGAg0HCNQIBOqyXgjUTOwCpbuDZHmKS6cx6SWQ1lgHAtUPhUDtqoVAm4XlZfsPm79OWp7i0rTGWgmkNc4DgeqHDiLQ4lZB/dQLgZqxFGitSzq8QA/Gm1dIs3Kbrc0sTWuslUBa4wIQqH7oEAIt2ayyl3oh0BrYCbTeJR1eoGJbJb6NSOlmIloJpDUuAIHqhw4g0LLt0vuoFwKtg5VAa17S4QUqeLJN9bgsrXFWAmmNi0Cg+qH9C7Q0YU8P9aYQaAdRWdi6l9QbgfJExsvSGmevIa1xkeAEOnRaQ+fEke6xs6ycPVE/KedwuPg9C2mNKZ+OqTqXpTUuKYG0xhkQ6NC4/QMZCgi0e1z8niUCnSTJ5v+ZLs3KqZRAWuMiwQm0RiF04eseiS6866jhdeGPbn51nNCR9qUCzUogrXERCFQ/FINIdtVCoGrYmpfUC4FS7tMe+vIWqCyBtMZFIFD9UExjsqsWAtXC1ruk3giUiHFrvzStsVYiRVrjAhCofigm0ttVC4HqYWtdUn8EyhqdZWmN9RISTGPKgED1QwcRKPYDrSwZokB9DatfJ6XRSfRYNg9ULyFBWuMMCFQ/dBiBYi18VcnwJtLXLdt/2MJKpLOLn0tWIiklkNa4AASqHwqB2lULgTYLy8v2H7awFl4Mq1MjlqY11kogrXEBCFQ/FAK1qxYCbRaWl+0/bP46fcrvdbJJSuVpjbUSSGucBwLVD4VA7aqFQJuF5WX7D1v4prENPuUWoKX7gWolkNY4BwSqHwqB2lULgTYLy8v2HxY70jsGAtUPhUDtqoVAm4XlZfsPC4E6BgLVD4VA7aqFQJuF5WX7DwuBOuaZ0HgK+Enuuww8ZQDJ9AUEWoOhv39gCbnvMvCUASTTFzH/bgAA0CkQKAAAWAKBAgCAJRAoAABYAoECAIAlECgAAFgCgQIAgCUQKAAAWAKBAgCAJRAoAABYAoECAIAlECgAAFgCgQIAgCXYjakGQ29mA5aQ+y4DTxlAMn2BDZWNYENll/ViQ2Uz2FA5HCBQI5EK1KHJBqo2WoE2jOp7WAjUMRCofigEalctBBpGWAjUMRCofigEalctBBpGWAjUMRCofigEalctBBpGWAjUMRCofigEalctBBpGWAjUMRCofigEalctBBpG2Nx1erKdZGy+W78KP4FAjUCgLuuFQJ1H9T0sBOoYCFQ/1EOBfpPQTb0QaPuo+asTmkBPf1Q/sO9AoEYiFWjVnalvftNgUAi0y7CGifSFqwOBDgcEamT1BPrNb5oMCoF2GbZaoMWrE7pA719Okhev8MePbpKe/ct36cOD8dYfPhwnyZl3Cm9Nk7NHd5Jkkxz0KSlxbp+V3mfFJsn5+ufdGgjUyMoJ9JvfNBoUAu0ybKVAS65O4AKd8vuhTHvzMb83ejWlSjxzeclb0+QrN9izK3fYD+LOoxv8huqT7V5vrEKgRp555o+D8s1VoskHUxBoV1dgGUN/WANg8zE9JfbkEZcpL9CDcfLq/tEHCX2VPN66m35+k40ukSfknfTRjeJbxLmnf0ScyRuhU/Ea92wiWqL9AIEagUB7pMkHA4H2j83HVBDoYhT+bMq64+RfIsOrtPvN7TehrxFlMiUejKkftbe4MmUJfqzow/fbg4dAzaAL77JedOHNxN6F1wTK7cfJHrNmJBen6JTrb025TWV3nUmT9+F77sFDoGZWTqAYRPJZoLENIqnGyx4fjEkZ9o98VX+Lt1qzULzVyfrwPffgIVAzqydQTGPyWaCRTWPSBSreYg9yAlXfKhXok23izp578BComUgFion0VSUxkT68Fmg62Xy37x48BGpmFQXaXb0QqPOovoetFmjVPVBFoPl7oGUCnSfn5/yN/oBAjUCgLuuFQJ1H9T2sYR7ohDuPOVEMtRNbnk11gepvlQuU9OE/WNi4HyBQIxCoy3ohUOdRfQ9rECibB5reH/OpSNo8UFWguXmgZQIlffiX+l4mCoEagUBd1guBOo/qe9iKaUxiImj2MLcSSRVobiVSqUDnSd89eAjUDATqsl4I1HlU38OaBKqvhX+TvPqKWAuvCVR9a4lASeiee/AQqBkI1GW9EKjzqL6H7W9H+gE2eoJAjUCgLuuFQJ1H9T1sfwLtfQweAq1BpAJt9bWGQLsMa5hIbxuWl+0/bG8CfdT3JNAUAq0BBOqyXgjUDARqwyTpfwgJAq0BBOqyXgjUDARqw5RvrNwzEKgRCNRlvRCoGQi0W44cehYCNQKBuqwXAjUTt0BrZ+WcdtQjv3/Z4VwnCNQIBOqyXgjUDATK6Eig6uL79kCgRuISaLaTDwRaVbJbgRo2u4pdoMNm5YRAeyYqgS72koRAq0p2KlDTdqsQaJdAoD0Tk0CV3cwxkb6qZJcCNW/43yxq4ALVshcvVrVv7bMuPN2ibpycebci4XFJjuOUFh+XFucr750pFAI1EpFA1Xw6EGhVyQ4FWiPlVLOowQtUyV4s1xJRkQqBfo2ojxyxPBloThMAACAASURBVOFxSY7jbOuRpFAcAu2brrNyNk+NGBadfXAdZOUc+rPqgPYfSlvMaY0X2YvFm2z/ECFQuovd76oSHpflOH6yTVuiRx+UFEcXvmcg0HZ09sFBoHVo/6G0xZDWOJ+9mNptse38PJGJN5cmPC7LcSxH8KfF4hBoz6AL37pe9Uh04ZWL4CRqcF34vECV7MWiDz/JJDhnrcaqhMdlOY55iuNUJIvXi0OgPRORQDGIVLciDCL1eA9U3faTvcuLCIFqdixJN1e2Oagi6UJxCLRnYhKoMoMGAq0qOeg0poZRoxIoTa0plKgLdGnCYwjUc6IS6GIONwRaVXLQifQNo8Yl0HlyXiiuVQtUXeMEgQ5KXALNwET6qpLdCtTAak2kzwn0yfbWf+WvqAKtSHhcJlBdkhDooECgLuuFQM2stEDTyel/UhIdz7PR96UJj8sSJMlB+xLfQqA9A4G6rBcCNbPaAp3LPUY0gVYkPC4TKC9OVyadL2mBfqf+L2YCAjUCgbqsFwI1E7tA9ayceYGS97kzNYFWJDwuTdEpVyKdKxRnW9efr/+rVQOBGoFAXdYLgZpZbYFm6+F1gS5PeFye45itheeL5XM1HN10mPsDAjUCgbqsFwI1E7dA4wICNQKBuqwXAjUDgYYDBGoEAnVZLwRqBgINBwjUSKQCxUT6qpKDCrRhVN/DQqCOgUD1QyFQu2oh0DDCQqCOgUD1QyFQu2oh0DDCdilQlxmKrYBAjUCgLuuFQJ1H9T1s7jodiBmayVe/3dp+PENxV/mP6wCBGoFAXdYLgTqP6nvYZQI1ZDWugbrryEBAoEZWSKB1dglqWS8Eahe16tKEJlA+rf3oN5fbGtTtsnYrIFAjqyPQWvtUtqwXArWKWnlpwhSo3BmkBRBoCKyMQOvtlN6yXgjUJmr1pQlVoFmuDSVjsTFHsSisZigWXfj7l5PkxSv1z9kJEKiRSAVaGButmaunZb0QqJnCRHrDpQlWoPrGH5v8fqYxR3EhQ7HcwD5LdNwjEKiRrrNyLqV5BsZAsfx8OsjKWYehP62+af2B5bJyqgKVSTMXO9UZcxRPkrPssZKhWEZ5dV+83iMQqBEItGssPx8ItBdaf2AVAmV7LWkZi005iuWOSuwNVaC8UO93RSFQI+jCu6wXXXgzq9OFpwLVs3WYchST0nyPOooi0KHGkyBQI6siUAwiKSX9Emisg0gsC7yeL86YYnNOf77I5+ArAtXTyPUHBGpkZQSKaUyLkp4JNM5pTFJ9asZio0DZYDvdWnkfAg2D1REoJtJnJX0TaIQT6SlaCuLlLdCcG4/+7U2+mT0EGgIrJNAe6oVAzcS9H2h+Hmj+HqghR7FgSlujuAcaApEKFGvhq0p6NpE+6LCmlUhaxmJTjmJ5NPupjsJPlFzIPQKBGoFAXdYLgTqP6nvYZWvh71/mkzZz80CrcxQTZ9LHj26ILjzNULyYB5reH2Mak29AoC7rhUCdR/U9rHE3Jn0lkjFH8WI8SWQo1lYi9bwxEwRqBAJ1WS8E6jyq72GXCfTld+R+oErGYmOOYv54U8xjYhmKsRbeayBQl/VCoM6j+h4WKT0cA4Hqh0KgdtVCoGGEhUAdA4Hqh0KgdtVCoGGEhUAdA4Hqh0KgdtVCoGGEhUAdA4Hqhw4jUEykryo5qEDjnkgfFxCoEQjUZb0QqBkINMfgyYuXA4EagUBd1guBmolboMpSTtMCdvE+T16srqH3BwjUCATqsl4I1AwEqr0vFmxCoBIIVD80GIEudgSCQLsM20Kgxv20IFC3QKBGIFCBsiclBNplWHuBmnd0hUDdAoEagUA56q7oEGiXYa0FWiOngJcCVbMWp/ffzLacZ+/L3Jv0uE9fSpSMHj4AgRqBQBlaXh4ItMuwtgKtk9XKR4GqWYvTO2KlPN3BLi/QbynlPAECNTJYVs4lNM+rGAeFD2KgrJzVDP0pDU7xI1melZMLVMtaPGfpjI/uME3muvAJ3bDu0Q2xO6gfQKBGIFA/KHwQEKiPFD+SgkCTBcoWoHJfZLb9EpHm+aJAz/Pjh0neUQ4EaiTSLnzTahd/Iq3qRRfeedTguvC6QLWsxbJQqUB5uaGyH5UTlEAfXxgJnnur5M21t9N0d3Sy1bmVAIFy1D9OCLTzsCsziJRLukmE+Zt//8eXkhKB8rchUAcCHRU9CYF2Xa3yxwmBdh52ZaYx5QRKB9oZEOgyWgj06ffZg8Ofr482Cm9SgXYABCpZ/HFCoJ2HXZmJ9LoQ56Rb//Lf//Nvy7rwECinvUBpS/PEXv5NCLSvaiHQ7sMOYLqOwhoEqiUk5vc+l9wDhUA5LgT6YJ09fHid3hC9zd9UuvD3Lo5Gx95g5YRodwpN1tqnC4E6rBcCdR7V97CmeaBq1mKZC2k+hkCX4k6gs3V2P3TtUqoLdJffJ90gnf1rvF3aon0aqUCxmUhVySAn0tcq239Yk0DVrMVPtpOz++nRh2P9Huh3Ugh0gbMu/IP10Ynb6WfXR1SOikDJ6y/sHd4a0dK7vOU5K3T5658uBOqwXgjUzIoJVMtaLJITb31AJ4WK93nyYghU0l6gn90ajS7Rbjm34g61piJQ3gw9vEbLiD68fQ8eAnVaLwRqZtUEqmUtpqPwL15h/Xn5Pk9eDIFKnExjOiUNmYrm5UKg2esU3odvM8IEgbqsFwI1E7dA4yJMgR57/l9TxYrshuhCoLotWR++RQ8eAnVaLwRqBgINh8AEmt0D1Z6yB8sE+vgCcWeLHjwE6rReCNQMBBoOYQu0Tgs03Vl7u9UcUQjUZb0QqBkINBxCFmite6D03Y1ZmwWeEKjLeiFQMxCoE3rJ5RmyQOUoPBGmPgq/w30pJtWTPvwtzahNTzdOgWIifVXJQQXaMKrvYUsEenT/TTp16eV3HDiOj8rLPfEW8FyeXRO0QCvngab31oU2d9ae1Y9reLoQqMN6IVDnUX0PWxTop9mOdg5mJC0RqLZCtDuCFqhpJZLot89K9m5qcrpeC9S4e0QX1UKgC5pcAM9N11HYgkCndNLnPm2HXnZg0CXzQiHQIgWBpg9fI558vmItPH+nTQ/eb4Ga9y/roloINKPRBfDcdB2FzV8nubU84WhS6Hk3BgLtmqJ3G+GzQGvsoNtFtRCopNkF8Nx0HYXNXSditoU0D8anWTJOJS/nwXjrDx8uViapb82T8/NxcubdYupO0YV/dJPdWU3TLBVd16yCQFuNwXst0Do5HDqoFgKVNLwAnpuuo7DLl3ISfsv+VfNyHozPXM62VNbfmidfG7NtlwupO7lAZbaQ8xCoQx623CjUKqlc82RcIdA65ZpT6iWVG/ozc0HPH6xjcknliuPlel7ORfZNKtpcyk66b9PvylJ3iox0Z1lZeiC68G7YKUv/0QgINMP531YrINAwyAl0kt0BzdDycurZN7W35mLMqSR1J31f7j3C1AmBumF3NDplvQyeEWkXHhPpq0oO2oWPeyK9FCgxnOhv63k5teyb+lvzRO39FwRKnssbpxCoP3gs0DaDSBBoVclBB5FWTaB6Wjlt2zr9rXmSJT7Op+4ULdRsaAkC9QafBdpiGhMEWlVy0GlMcQtUvwc6sRJoMXUnj3qfDz+9sg+B+oPXArWfSA+BVpUcdCJ93ALVR+G5QNWZnDmB6ik7ZfakQupOqeWjf6MTnM5CoO05bHfrM8NvgVoDgVaVHHQpZ9wClYk3ORN2D1R1nSZQ/S0h0LLUnWq7dkpbqxCouv+8xUSkexfp8qPdlkPwKQTqtl4I1EzcAlVXIqWPtuljNS9nLnWH9pYQaFnqzqmS9IP9hEDbCVTsaQeBLgMCrSoJgXYnUL4W/ndsT6ZETv3M8nLmBKq9lQm0mLpTjMLTso9uiC78d+qfvzVeC7TNCszcpqAtgEBd1guBmoldoHKsh2Xi5O1LJS9nLnmc+pa8B1qSulNbicQCTORapk6BQI1EKlAs5awqOahAG0b1PWzZf9X3b7L9QL8tZyUpeTnz2TeVt7RReD11p1wLT8puinlMLJdn14Qj0Bnvxz9YJz9moxOf/Hhd7sOUpg+vkyfP3ebFNmbro+N/y3r+l0QX/uF18uS5twqF650uBOqwXgjUeVTfwyKlh2MsW6Bs/3nSsNxgOTy+u9gJVG4Lypqcs9GXybOn/0EV6APx/ka+cL3ThUAd1guBOo/qe1gI1DGWAiUa3BD5iWcjtkDz4bURLfL4An1yeIs1UclbJ26nv9IGkXZGJ9n7hcL1ThcCdVgvBOo8qu9hIVDHWIzCixxHT/+/F0Qzk7/C26NypJ39FD19VaAiJyd/RStc73QhUIf1QqDOo/oeFgJ1jK1AiQHFI2lJ1iA9vJZlNyat09mIt1sVgZKHx8X9z1QvXO90IVCH9UKgzqP6HhYCdYz1KDxpePKXeEc+5RnhFdGSd+Vbahee9vhHx17fSzUr1x3jh0Bd1guBOo/qe1gI1DHWAiVS5HZsKFCWIokmT9qDQJ1UC4F2HzZagSr7g9AJmyX7K4dEUALdzUbSdYGq40GlAiVP/+U11v9/3Hx7+kgFion0VSUHFWjcE+kh0LbYCpTY8v9eZ/6TNzrFPVB1StISgabs8dPvW8yvX1GBVu4yBIF2GbZCoKVXJTSBOkgG7w0BCZQNue8wIc5ES5SPwu+oHfsSgdJmKn2J/dzJ3wUwn+5KCrR6n0sItMuwywVaflUg0OEISKBMeQ/WqRfpqNALe+nDi8yC5LUTt9P043Uxx14K9BtpNgpP3394TUyqXxSud7qrKFDDTusQaJdhlwp0yVUJWqBiEbueyljJWlx46zJbxclQMh4PhdcCXUxjWty93OUjRceeVXZpkouLTqVKy3KH3TDVViIxIauF653uCgrUlOsHAu0y7DKBLrsqMQhUS2WsZi3OvTVdkvF4KMIRKO+801fZeqRP3iP6fF30wtnydj7XMxPo4XV6lFwLv74orRSud7o2WTnd0jyPY7A0+FTqZeXshqE/piGw/axyWTnLBaqmMtayFutvkWev7ovExVrG46HwWKAV1L+B6QAItE8afCoQaL/YflYFgWaD8HT8vSSVsZa1uCzLMd8sWct4PBQQqBF04V3Wiy68mdi78GUCVVIZS6RAtSzHi/66nvF4KCBQI5EKtLraan9CoN2HXbFBJH0PUCVr8dIcc3rCzqGAQI2spEAxjak+Pa5EKr8q0QlUzVoMgRaAQPVDvRQoJtLXL9xJ2FWZSF8iUC1rcYVAfZhPGqZAe2VFBdpRvRCo86i+h20qUD1r8dIsxz2l3TQAgRqBQF3WC4E6j+p72KYC1bMW57Mcn80O0jIeDwUEagQCdVkvBOo8qu9hmwtUzVpcyHL86n56fyxmiC4yHg8FBGoEAnVZLwTqPKrvYRvfA9WyFufGl6aLCVBaxuOhgECNQKAu64VAnUf1PazdKLzMWpyf4VRYCy8XyQ8DBGokUoFiP9CqkoMKNO79QOMCAjUCgbqsFwI1A4GGAwRqBAJ1WS8EagYCDQcI1AgE6rJeCNQMBBoOEKgRCNRlvRCoGQg0HCBQIxCoy3ohUDMQaDhAoEYgUJf1QqBm4haompWTz43P9gLJZjg92d7az2XvNDPIvqAQqBEI1GW9EKgZCPRgfD6f/tgMBOonkQqUVVu55VIn9UKgBuQliVigug7LBDrN7bzkLxCokYgFWr3pZyf1QqDVZJdklQV6dGNrHwJdCgSqHzqYQA3bzndSLwRayeKSrLJAaQ++KNBHNxOZxHienJ+PkzPvapmNRRf+8zvklXP7E77fiJ4T2T0QqJFoBWpKfNRJvRBoFcolWWWB0h58QaBi65BNugnoPPnamN0ZVTMbc4Ee8FfOfIsLVMuJ3AEQqJEes3I2z5QYIM4+rZ6ycg79efVANx+cpJCV0yTQoxs8a7EmUL553ec3E7FnPXnyOz2zMRPo0Y3kzF36SklO5C6AQI1AoG5x9mlBoK7o5oOTLE9rLJqMeYEejM/q5ehTuX0y21J5LnLBa5mNp/wdHm0qBarkRO4CCNQIuvAu60UXvgrlkkTchTcJdM565LpAswQebI87oUk9s7HYpv68rOXqknTJToFAjUQrUAwiLS+JQaQB74FO2Au69JQpovTWJ2+O6ok5qUAXiZLEIFIuXbJzIFAjkQqUfq1t/QmBdhY2uySrK9An22cXTwpHsQcVApUHQaC+ELFAMZF+WclhJ9JHvhJJF6giN+473oOv1wJVi6AF6icxC7T/eiFQM7Ev5dQFqqQn5l6clEkvfw+UCVTPbKzdA+VvQaAeAIG6rBcCNbNaAs3G16n0zvKNRHg5TXqTzJlnF5mMtczG2ij8PIFAPQECdVkvBGpmxQR6ME7O/P/k528ui81F5Dh61TxQLk4ts7E6D/TXYwjUFyBQl/VCoGZiF2iiz2PKlhPxyZ3TbEu7qpVIotGqZjbWViJt/QAC9QQI1GW9EKiZVRNo+vmHL5HHL36b99GFG4tr4d8khV4Ra+FFITWzsbIWfjNbCw+BDg4E6rJeCNRM3ALtB318qTsgUCORCtShyQaqNlqBNozqe9heBSoXdyqzSzsFAjUCgbqsFwJ1HtX3sL0KdM52D0nvj3vanh4CNQKBuqwXAnUe1fewvQqUdN058iZpx0CgRiBQl/VCoM6j+h6253ug9+lY01ev9ONPCNQMBOqyXgjUeVTfwyKtsWMgUP1QCNSuWgg0jLD6dZom2TSlRA6Us93oVOS0Izof/is9tSXtgECNQKAu64VAnUf1Pax+nbLhcTrjXQz0TPMZN7KNQbOpor4CgRqJVaC2OzG1qxcCLaV4MWIVKN/pOKXW/Cvh0sUedItCfFGS583PFAKtQaQCtd4LtF29EGgZ+sWIeyK92C/p6EZy5YbcLz4/ZC53Vu4sF5wzIFAjcQrUfjf6dvVCoCXkLkbcAs328jz9kei6z3k3XclQzAQ6lzsl84F1vtKzNKHxgECgRqIUaIt8SK3qhUBLyF+MuAUqboJSjwqXTlmnXs1QrAv0jjK1szSh8YBAoEZ6y8rZPJtiaLj9vLrMyjn0J9UDDj+tanJZOcUqddo95zvbySzGSoZirQs/TzavkFJ3mCxLExoPCARqBAJ1htvPCwJthcNPq5qcQPmYOxs4ktvGn01zGYo1gS5ump5fktB4QCBQI+jCO6wXXfgS8hcj7i48vwnKO/JiE/mr+QzFZYNIUqAlCY0HBAI1EqVAMYhUXRKDSN0JlHXcp4uc8BPeaVcTbOYFevSbf//HlxIu0JJ8nAMCgRqJU6CYxlRZEtOYuhMoS5jJ3UhFyScxVQn005fEOxAoAwLVD8VEertqIxLoCk2kT9lNULlWkyiS50AqTWIsB5GSzZf//p9/e0MT6MCDRxII1EisAnVnsoGqjUmgbaL6HrYg0IPx2XmWTvMsz4Gk7yCvCpTf+1zcAy1JaDwgEKgRCNRlvRCo86i+hy0I9OjG6X/KNo7f+kFJhmJVoDKL53ysCFQvPiAQqBEI1GW9EKjzqL6HLW5nN8kmwNP9j6VKlQzFukCTs/vp0Ydj9R6oXnxAIFAjEKjLeiFQ51F9D1sU6Hwx9DPN1hKpGYq1e6BTsQ7pAz7nqSSh8YBAoEYgUJf1QqDOo/oetihQ0qiUHe/5YhRdyVBcHIV/8Qp3Z2lC4wGBQI1AoC7rhUCdR/U9LHakdwwEqh8KgdpVC4GGERYCdQwEqh86jEBbfa0h0C7Dxj6RPiYgUCMQqMt6IVAzEGg4QKBGIFCX9UKgZiDQcIBAjUCgLuuFQM1AoHU5GjxlEgRqBAJ1WS8EaiZ+gR6Y5r8btvkU05zuXx58PScEagQCdVkvBGomfoFOTZso1RKoDwviIVAjcQq0zV5MEGiHYemFiV2gxH8vtXIfBBoQUQq01W6gEGh3YbMLE7NA58lWu1QcEGhAxCjQdvvRQ6CdhV1cmJgFynYBzfrwn98ZJ8m5/QnPGcezFgu/3r/MFnGmWS5PoU7271Rk5dTf6jnvMQRqJEKBtsyIBIF2FVa5MBELlJpO7vLJBpQoZ77FBcqzFnOBTrON6JsItNe8xxCokd6ycvbHAKkZO6DLrJw69VNdBkhnn5okn5VT3xWEmPTMXZqfWMtazARK1PrqPnmH+rFEoLILnxdor3mPIVAjEKinQKBO6OxTk+QFyr0nk3LI7ZimQqBK1mLeDJW5j2sLtNe8xxCoEXThndWbogtfjXJh4u3CC+FNuNlk5k3SYryq6vSsPkbUQKC95j2GQI1EKFAMIplKYhCpO4GKNiE33cKSYhCJ646W0RLHNRBor2k7IVAjMQoU05gMJTGNqTOB0iweSTa+k7UUIdDaQKD6oZhIb1dtlALNLky0AhWj7ixLx36HLdB+8h5DoEbiFCiWclaWHE6gaexLOSdyVIcP98h7oNyGqkBt74H2mvcYAjUCgbqsFwI1E7VA+WCReHR+MWw0T/IClaoVU5rk4HqJQNW3es57DIEagUBd1guBmolaoEoWuYnow9N5oL8eFwXK5oGm98f8XqmcLqoJ9Dtp/q2e8x5DoEYgUJf1QqBmohboZDEvkzc6xT3RrR8UBCpXIolBe8arNxYCZfnlz+fe6jnvMQRqBAJ1WS8EaiZmgR6MF/cmSdORupGuhd/M1sKrAlXWwpPHb9LHR6pAj25yu6pv9Zz3GAI1AoG6rBcCNROzQJfiw9ZKFkCgRiBQl/VCoGZWSqByqaWyPVNIDCLQ0HgK+Enuuww8pcoG84SOFNGhok7XrHcFBFqDob9/YAm57zLwlCobZAuTOp1t1BkxZxwFAPgPHQJKvnolSH9CoAAAYAsECgAAlkCgAABgCQQKAACWQKAAAGAJBAoAAJZAoAAAYAkECgAAlkCgAABgCQQKAACWQKAAAGAJBAoAAJZAoAAAYAm2s6vB0LuBgSXkvsvAUwaQTF9gR3oj2JHeZb3Ykd7MSu1IHzgQqBEI1GW9EKgZCDQcIFAjEKjLeiFQMxBoOECgRiBQl/VCoGYg0HCAQI1AoC7rhUDNQKDhAIEagUBd1guBmoFAG3M0VEYlCNQIBOqyXgjUTOwC/fU4Sb7i1Hj3L18l/z7Z3nzXZdQ6QKBGIFCX9UKgZiIX6JwmMXaaBP7oRgKBekufAv0iodGxbqptfrAP1fYn0OrL0o2X4xXo1HHzEwL1mx4F+sUvNjQoBKo+b3Z4ZUmtqOGyQKDNBDpJztcPXAsI1Gf6E+gXv9jUoBCo+rzZ4ZUl1aKmywKBNhEo68Anpz+aJ+fn4+QMMd6jm+Mkefkuf5s+2Ty3P6FGPBif/oi+JsWoFDwYb/3hQ/LszDspbdJSrvJy5B3evnXv6dJfroc68kCg+qHy2C9+sbFBIVD1ebPDK0vmbqtUXhYI1E6gXxvTnynRqBBgSsXIHm/9oESgasGD8ZnL/Nn5nECPbnDb9tQchUCNPPPMHxvwxWFpcqqhUxBo3QNxKXrlKbEnj7xOvGlIRLp1N/0dEV1ybj89+iChviNPztylT5KiQLWCVLSv7qePblAF6134KW95zpOtPqY2QaBGIFBPgUDDYJlAeQtxKgbk2c9pwpU5LRGoVpAIlGnyYEzf0gQq+vD99OAhUDPowrusF134umUbFPU7bPkg0py7Uva4ufek9UhrMy9QvSAXp3SmJlBesK8BpaAFerjnKlIVGERyWW94AsUgUsuwywTKGopElZLTHwkRsjJ5gWoFc41TfRSe9eF76sEPLtAH6yPOX75ebcPd0cn8S/cuXip/o5yfk6r+wkK5kU5jwkT6qpKDTmOKfCJ9lUBls7GNQJ9sK23ZrvFGoKPR2ttVBxU9eXht1ESgM1pHTddqRDqRHgKtKjnoRPrVEqjS1a5ugap98iqBppPNd3ubEjq8QJ9+n/48/MVFg0ELCIHWZdeq+ZliKafbeoMUaM9hV0mgC2cu3pKv5u6BqgUrBUqnmLpdK7ocXwTKfNisfdhQoDujjUbhMyBQl/VCoGZWSaDkGf/JnouRJTrH6WqajRRN2YC9VrBSoKQP/4Fq2y7xR6DkIW+CPrxOuvXP3U4XzpuNTuyJnvq910hH/Bi9X7rL+v2XZBf+4fWROIoEOvHJj0mM428t6mEd+NHT789GG7P10fG3tQNIiMP3RqO1N9L0Y3LcKb2lCoG6rBcCNbNSAj0Y0/mg6adsXhIx4ZkfsSdUgPQZnxUqpn4uChYE+p1UuR0w2XyJv909HglU+HIm7opeotY7mb3BPfmeuF96Yi8nUHHU2iUW8/hFXmwjq2ch0C+v05/aAaR3f409e+M9GV09XQjUYb0QqJmVEmi2wOgcffKEry86/S3WguSrlpJXb2grkWjB3CKlCVuSlAl07ni3p6pfrqd6VJYJlKnw8QXaAjy8Re+IPr7A3nx8gTxmb85YK5G2Fi/pg0gP1kcnbqefXWf3UenA1At76cNro0XsTM8jWvBX+gHExU//JxqPhd/N3YyFQF3WC4GaWS2B8iXubFE74ejDl5LkFb4WPk3vv5kkL16Rg/NKwZxAj25SZWYC5dNIe8Engc54w5K3OtnPHabIxeuiT09Ut6ELdEe0GneETTd4bNWEUqD8Ne0AoUxxXP7eKgTqsl4I1EzkAq3DpJUBn2z31YP3TqCH14T0HqwTw/E+PNOoOlupINDMecy1Upys5ZohBcrq0w/Y5TaV5XPDTZEKFBPpq0oOKtCGUX0P279AexuD902gJ2kPXkLeYH143pGXAj38xU++9+woJ9BMlSycjFkuUM2VvKyILe4YQKBd1guBOo/qe9jeBfqox31BfRLobkGg6Y68+yn+/fjZUTY8pAlURGEPaglUPQAC7a9eCNR5VN/D9izQieuEIZX4JFAqLl16xHcb6q3O2Wi09tzXv//LfBceLdB+q4VAuw8LgZZQJ/nmNKHb3vWFRwJlty5zIziPL5z4L7yEuNW5QV813gM1CjR/DxQC7ateCNR5VN/DuktrzJNv0OlUzQAAIABJREFUTntsYBrxR6BiJZIcHhem23n6H7jd1J76bH3JKDyPUUOg+gEQaH/1QqDOo/oe1plAxYIjCFR5nK2Fv3eRj4/zCZp0RdAGfX0mNxkRN0hP7qWHdJXRBpPfN9LyeaBmgebmga6uQJtuX9K2XgjUedRG29FEIFCvGF6g+d2Y5EqkU+wZcSY33i5vKvKVQrdEY3WULVHSVyKZBZpbibSyAm28gV7beiFQ51EbbYgIgbrFG4E+95ZcP8nWwmfr2KXNFqPwx94QGjy8Tvenk2vh6SL558Va+BoCVQ9YSYGyr3XzLZzb1guBmrGfSG++nh4I9NHNJElefkd9wjJtkq750Z0k2bzCF8OLkaBFKk6ZO04k/6gunKumM4YWaABELFCLJCJt64VAzVgLtMb1HF6gIvGmSP3Gn2zye5tfucGeXbnDU3Pup1oqzpxAqwvr1XQHBGqkWVK5fmme6qwjhvjlrZPK+c5T4jeJ5ArmkspNkrMsuSZdbcl3WPr8ZsKzxiWnf0T76axdOZVpOhepONVBJGNhtZoOgUCNQKA1GOKXh0DDuIK6QOX2H0yGk2xT0LPSgjLhJi+gpeLUBVpdWKumQyBQI+jCu6wXXXgzUXfh6Saf7ywec72xrZmmepIPummTnopTF2h1YbWaLoFAjUQsUAwiLSsZpkCDGERim3y++G0tIRLbnU40IOVWShO2w6eaSU4XqKGwUk2XQKBGYhYopjEtKRmoQIOYxnSfb5r8yv5i2zn2wK1AlWq6BAI1ErVAMZG+vGSoAg1jIv3Rv72ZaDsgL2+BqvsqGQWa24RJVtMlkQr00C4BZymRChRLOatKhjqR3sew5RPppywPvH4PtOBEfQzIINDSAaNpx8PwcQr03sUm+ToNQKAu64VAnUf1Pax+nWQyDvZzkuU2LneinorTIFCtsFZNh0Qp0IYJjw1AoC7rhUCdR/U9bGEUnibXfMScmZsHWnRiPmcnTb65VKBqYa2aDoFAjUCgLuuFQJ1H9T3skpVIzHz6SqSiE/WcnTz55lKB5vJ2KtV0BwRqBAJ1WS8E6jyq72GLa+GJ2zbFBKNHdJznFbkWnv7Qnajl7OTJN5cLVCusVdMZ4Ql0NjrxCd3Qju8Dkqb36KYgx17fY29tzNZHx/+WZ4xnaekouc1BGp8uBOqwXgjUeVTfw7rbUNlDghTodxc70aXvid2cqCxnoy8Tsz79D1ygMsFnLktI89OFQB3WC4E6j+p7WAjUMW0FOhqd2ksfXmMbMM9Ga2+QPjvR6CX21onb6a8We9Vv8ANOtJrUBIG6rBcCdR7V97AQqGNaC5Tt3skTI+2oWZJmYlNmIVDRh2/Zg49VoK2+1hBol2HbTKQ3lu0/LATqmLYClVvXKy1LKVCRH4QLlPfh2/bgIVCn9UKgZiDQcAhRoMKbWTqlX/zke8+OuED5W3IUfld90RoI1GW9EKgZCDQcghcoTfLB2CgK9PEF8rxtDx4CdVovBGoGAuUUFrd7SOgCpVk7n/v69395rUyg6c7a26178BCo03ohUDMQKAcCLaetQEUmeapLfu9zcQ80J1A6MZQPObUgToHa7cLUvl4I1EwjgbLd5GufAQTqmBAFqjhTJtKcrZcKlPThb7VelBSlQC33AW1dLwRagyYCbXohIVC3BCnQ0Qt76cOL1JaPL4xO7qWHdGXShibQb/DCO2vPivZqi9ONUKC2O9G3rRcCrUMDgTa+kMMLdJ6cn4+TM0SN99/MNo1fvKhkJmYCZck8KJOuE2xaEaJAj/FxI3Zvc1esQ7pFe+rZ7dGd0UhOom/dg49RoNa5kFrWm0KgbqM2v5A+CPRrY7bHxx2xfTwVZPaimpmYCVRmOvK0ORqiQE988h7R5+vclXQU/tgb3J2ZQA+vC3GSFmrrbUV8zsppSR+5GLsnsqyc9RNoOqOfXyyX1nie0I3mfkd+0oTER3eYLOWLWmZi7sypyCAvNvv0jCAFWn9ep7xH2gYI1FMg0EAFukikmbJNPs8vXtTSGHOBij68nz342AXafgweXXiH9abowruN2vxC+tCF17bolAJlL+ppjLlA+Wue9uAjF+jD1pNA0ygFikEkU8lABBrmIFLWFz/6zb//40sJF6hI864m1hTSnCoFvCNmgdKhpPYN0CgFimlMhpKhCDTAaUyZCj99SbjSINAn2+Q9T3vwUQt0l+1715ooBYqJ9NUlgxFoeBPp51nqt2Tz5b//59/e0ASqdtTls8nmu7724AMUaO/EKVDsB1pZMhyB+h+2XKD83ufiHqh8UclMLK1JJ4l2nBvOGgjUSKQCxVr4qpKhTKRvEpaX7T9suUBlNqP5WL3FqaUxlgIlffgPSlK+ewEEagQCdVkvBGpmRQSanN1Pjz4cq/dA9TTGWb99svlSx8k1rYFAjUCgLuuFQM2shEDTqViH9AHtnWcjS2pm4kyg88TXHjwEagYCdVkvBGpmNQTKRuFfvMKfL2YpKZmJM4GS1qqnPXgI1AwE6rJeCNRM3AK1QN4v9RAI1AgE6rJeCNQMBJrD2zF4CLQGEKjLeiFQMxCoziNfJ4GmAwk0NJ4CfpL7LgNPaaWLSeLvEBIEWouhv39gCbnvMvCUVrqYJnSHO1+JOeMoAAB0CgQKAACWQKAAAGAJBAoAAJZAoAAAYAkECgAAlkCgAABgCQQKAACWQKAAAGAJBAoAAJZAoAAAYAkECgAAlkCgAABgCQQKAACWYDu7Ggy9GxhYQu67DDxlAMn0BXakN4Id6V3Wix3pzWBH+nCAQI1AoC7rhUDNQKDhAIEagUBd1guBmoFAwwECNQKBuqwXAjUDgYYDBGoEAnVZLwRqBgINBwjUCATqsl4I1EzcAj0Yn/5o8WxazLipF/AcCNQIBOqyXgjUDAQKgVYBgeqH+i3QLxEc1guBmtEFWnoBbMLysg2K9iHQEiBQAxCofugwAq1Z7Ze+VPYHDIF2HlYWLb8ArcPWKQqBmoFAjay0QL/0pdI/YAi087Ci6JIL0DZsraLdCfTTl5LkzDv0mejCf35nnCTn9ifJ1XwBz4FAjayyQL/0pfI/YAi087C86LIL0DJsvaKdCfRbCYPIUgj0YMxeOPMtIVClgOdAoEaeeeaPofOlIenstyoItLOanBHF596Up8SWEuIyUVm+up8+upFs7QuBHt1IztxNjz7gztQLeA4EagQC9fQPGQId5nNvSlGg5/nPzXeFQOcJv+s5lQJVCngOBGoEXXiKq3rRhW8UddkFaBm2XtGuuvDci0+2M4FOuDHJS1ygagHPgUCNrLJAMYhUp3AnYaMeRKI/FwIlPXhxtzMbRFoU8ByvBfr4wkjw3FtOz+DxhbW3axdeaYFiGlONwp2EjX4akypQaUoItA4WAh2NTro8AwgUE+mrS2IiPVqgtfBcoE+/zx4c/nx9tOHwDCBQLOWsLumRQJ2F5WX7D2sUaHYPlJsUAjXQXKBpujs6sefuDCBQCLS6JATap0DlKPw8gUBrYCPQB+vs4cPr66PRc7fpK7PRxmx9dPxt8ppyk5Q/uc0POfHJj0nx4+Kte6+Rt469vpdCoBQItKokBNqnQMU80F+PIdA62AuUGJNxKaUC/TJ59vT7D8RrG7SYKLB2iR1y/KLy1nviZiptyUKgEGh1SQi0T4HKlUhbP4BAa2DdhX98YXRqLz28NaL6mxEX3k5/le6MTrLXaFEiU/LaZ9dZAWrWF/bSh9fYW7PR2htpevgesy8ECoFWl4RAexUoWwu/qayFXxTwnDAE+tkt5r1dMRbPfs6YJaULD6/RAjviTukOLfBADDw9WKcldvgTUm4DAqVAoFUlIdDOBFrBYjg+GDwX6GIa0ykqP6G9B+vEkzPWsKRGlDc5hUVTKldSgIszZ0sIVAKBVpWEQPsUqNxVOaiN7DhhCPTY8/+aaj4l7pyJ1uZsVBwbYndMxbjT4tXDX/zke8+OIND21UKg3YddJYHO2e4h6f1xcXt63/FcoNk9UP60TKDpPT5U9Pzeojx7kBPox8+OsiElCBQCrS4JgfYpUNJ15wSw/VKOsASqam+2mBl6+C+vsbVKVS1Q0lBde+7r3/8luvAOqoVAuw+7SgIljc83iT6/eiU4fwYl0OwWJ2OmT63fJa3S/D1QRaD83ifugbqpFgLtPuxqCbQdR8OJNySBZoPszI9CoFKT7KcoQCx5MtUFKkPN1iHQ9tVCoN2HhUD5yvga3L883Nh9UALl0zzTj5kEZ5ks6WsPhTO1eaCaQNl0UboyaQMCbVstBNp9WAi0rkAHnfwUlECzlUin0kUXXq5EYkX1lUjqPdBdsQ7pFhUtBGpTrbItEATaedglRUs3F4RALWtoT1gC5Wvh+bzP7B4oe23tdfGEDic9L9bCF0bhj73BD4NALapVN6aEQDsPW160fHtrCNSyhvZ4LVA/iFSgTb/W2tboEGiXYZdPpF+SYCUogU6Ts0d3kmTzSpp+ynIZs1cf3UyS5OW7vIia5Ji+NZZvzZPz83Fy5l0xbP/it1laOpnAUynYGxCoEQiUoifngUC7DLtUoEsyJIUm0K/waZ9X7izmfs75biKbzJhakmP5Fn+cfI08O/1RemcxcTQTqFqwNyBQIxFk5RQ0z+zoGqe/ToBZORUC//AbkMvKSYR3+kds7jxthE4TumMIUebW3fTzm+zJk201yTF5Rhqp5Bl9a57Qcr8jP+mxtCF7NevCawV7AwI1AoF6+jcMgQ744TegIFBmOJG8mNtvItYgTfj2yvwJ315ZrpMXOy9zO4ot7MnB5zOBagV7AwI1gi48ZfF32K5edOHNxN6FZ36Um9VRF2bDQMydWpLjLOHcwZi8JbeuF6gC1Qv2BgRqBAJlaH+6EGiXYaMfRKI/nmxzF1JdZjt/0u2Y9BRzxKISUn6+WC1/9Jt//8eXkoVA9YK9AYEagUA56p8uBNpl2Irt7Mr8GYNAhfPoAz3J8RKBfvqSeBEC9R4IVKD86UKgXYat2g+0xJ8xCLSiBaqOCSm3Rzdf/vt//u0NVaCD7F8flUAPHSbuXBCpQLGUs6qkrxPpQwxrFmj5PVD2qj5LXgiU3/vM3wMdZDp9WALdETk9KDPlMefexUtpB0CgLuuFQJ1H9T2sWaByFJ5IsJDkeJI1OtkgkhiAEiXGyii8VrA3whKoyIPE2MmvxtR3u3MHBOqyXgjUeVTfw9YQqDYPNJ/kmL5FFy2dTxcCTc7up0cfjuU90O+kuYK9EZZA5a6eKV3hfmKv8CYE2k+1EGj3YVdKoPpKpEfbSpLjbIHRuXTRupyKdUgfsFgTPpikFuyNsATKsxszZplKJRBob9VCoN2HXS2Bpo/o2vZXxDr2o+Ja+DPv0IfaKPyLV8Tzo5sJi6kU7I3ABPr4gpSk6ME/vD4ajZ6juy/x/eoupWJ7JvaafP+tJeHqnS4E6rBeCNR5VN/Ddr8j/YAEJtBsGEn04JX9PzOByk1D+Z6gWSI5+9OFQB3WC4E6j+p7WAjUMW0EKjf5nEk/LnagF1140kg9tZce3mKv7bB96G+N8vuKNjpdCNRhvRCo86i+h4VAHdNGoHIYaYcpUSZJYu1SIdBd0UbdXaTpbHd3NFKBtvpaQ6Bdhq2aSN8iLC/bf1gI1DGtJtLzjegfX6CW1LNw8meH17LUxif2yEvHW93/ZKcLgTqsFwI1A4GGQ3AClVneL6VpLg88FyjpwUvIazP689jrrVYoQaAu64VAzUCg4RCcQHl3fYd13bOcSexBmUDTexfZw+dbKBQCdVkvBGomboEOtGi9I8ITKG1tPr6wQR+Wt0BzK5QO/4Xmmcsv+2wABOqyXgjUDAQaDuEJlHpyxiVZfg+0ZMBot80wfJwCLdvVp496V1Kg2T7UECgE2p6WuzHNRn/xXbEeSYzCE2kuRuHlyDyVqpz0JH/anW6MAi3dV7KHeldSoNmHDYGmEGh7WgqU3uXc4A/z80C/kb2WfrxOCpGX6OOH19CF1ynf2bz7eldSoIsPGwJNFwLNEhnLjejEdkr97qbUlgAFqnbIlZVItO3JzCpXIp1KFyuRMJFeY0lunc7rTVdRoMqH7bnpOgpbLlBl+5CpTC/H3pj2uptSW0IU6IP1RXvyIR0hep6vez+8zgeL2Fp4Mf+TPV5rNY8pnqycGcNnanTBMFk562fBbE0vv0/35LJycoGqG9jxNHAH40RLDhcGIQq0ZyBQT4FAw6BUoGoiY74x0zz5O741aEg9eAjUDLrwzupN0YV3FVUr6nfYsi58PokH3Xp+84c8c3Gfad1bA4EaiVCgGEQylRx0EKlWVLWo32HLBKqlkWPSPLqx9XvaEp0MktrIGgjUSIwCxTQmQ8lBpzHVi6oU9TtsuUCVRMbkn639g/FZ0gh9N3sjECBQI1EKFBPpq0sOOpG+ZtRFUb/Dmlug1Jxz0vKcJucD68FDoGbiFCj2A60s6VagNmHjFqh+D5SY8ypxKO3KT8PqwUOgZiIVKNbCV5UcVKCrMJFeS2RM2qF/RXrx5K0zl4OaxASB1gACdVkvBGpmFQSqJTKmHqUipT+CmsQEgdYAAnVZLwRqZhUEqicypnmK6YNJEtQypBQCrQEE6rJeCNTMSghUT2Q85y1R8SMgIFAjEKjLeiFQM3ELNC4gUCMQqMt6IVAzEGg4QKBGIFCX9UKgZiDQcBhEoKHxFPCT3HcZeMoAkukLCLQGQ3//wBJy32XgKQNIpi9i/t0AAKBTIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLsBtTDYbezAYsIfddBp4ygGT6AhsqG8GGyi7rxYbKZrChcjhAoEYiFahDkw1UbbQCbRjV97AQqGMgUP1QCNSuWgg0jLAQqGMgUP1QCNSuWgg0jLAQqGMgUP1QCNSuWgg0jLAQqGMgUP1QCNSuWgg0jLAQqGMgUP1QCNSuWgg0jLC563QwPv1R/cBlzJOt/XYR3AGBGoFAXdYLgTqP6ntYCNQxEKh+aM8C/QKhZbUQaDdhxaVpGBUCHRAI1EhkAv3CF/ifKSbSV5UcRKDapYFAlwKBBkVcAv2CAAKtLDmEQPVLE7lAD8Zbf/hwnCRn3uGv3r+cJC9eWbyfpk+2N99N02ly9uhOkmyStz4lxc9RcxKB/uHOONl85S4/9tFN8s7Ld/nBS8KSN7h0J8n5+r+WGQjUSFQC/UIGBFpVcgCB5i5N9AI9Q9xGYT6bLh7nBfqVG+ytK3fYD6rBeSKO3bxKC87H/OCraUXYoxs0mozqDgjUyDPP/NFXvtArQ/+2eQoCHfqEqoj7UlTylNiTR1wmKdAkeXU/fXQjEc9e3T/6QDzWBZqc/hHRH2+EThP62jzhx15m5Z9s03YpOZi+tTzslCvVdfcfAjUCgXr6VwuBhsEygZ7nz0RHPaWtRNqKzAuUtRhFcV5iLtqX5Nl5eaz4WRWWmdNxDx4CNYMuvIN6F0eiC7+E3KWJvguvdKm54rT3FwJl3pM9b+a/eSKGoWhzUvbNuSGXh+XlXPfgIVAzUQkUg0j1KsIgUucCVTSpaa0wiMSf8BeFQM8uipIevIQUWR6W9+GdD+BDoEbiEiimMdWqCNOYohPok23iTtc9eJ8E+mD96ffbBZ6NTuy1i1BGZALFRPo6FWEifTgCVS1ZIdB0svmu8x48BGomNoE6qBYC7T7sKgm08h5omUC1e6DKsRVhaenzmXqdAYEagUBd1guBOo/qe1izQIkXmdjEQDpvJfLx93KBcjHyUfiJuK3Jbm8uD8v68B9oRnUBBGoEAnVZLwTqPKrvYWsIlE3YTO+Pqd+IFs/cpfM6qwS6+Z1sHig5dusuW6d0viosPXjzpbarSIu/nON4dagU6IP1E5/8eH00Ov4Wf/XexdHo2BuL99P08YW1t9N0d3Ty8L3RaI289TEpfoqakwj0k/fWR2vP3+bHPrxO3nnuNj94SVjyBpfuzmhjyelCoA7rhUCdR/U9bA2ByiVDTJZz/vjVG8sFKlcisaaqXIl0Lq0MywK77sH7KNDjxG2UDfri7uJxXqB/cY299cZ77AfV4Gwkjl27RAvO1vnBl9KKsIfXaDQZtfR0IVCH9UKgzqP6HraOQJW18OTxm/TxUYVA+Vr4c2JGElsLz1e/V4Wla5Zc9+B9FOho9MJe+vDaSDx7Ye/wlnisC3T09H8i+uON0N0RfW024sdeZOUfX6DtUnIwfWt52F2u1OXdfwjUZb0QqPOovof1Zkd6aWGX+CjQDf5MdNRT2kqkrci8QFmLURTnJWaifUmebchjxc+qsMycS3vwEKjTeiFQ51F9D+uNQN2PwXspUKVLzRWnvb8QKPOe7Hkz/81GYhiKNidl35wbcnlYXm55Dz5WgWIifVXJQQUa90T6wXjkfBJo6qVAFU1qWisMIvEn/EUh0JOLoqQHLyFFloflffiKAXwI1GW9EKgZCLQDJkkHQ0gQKHuJuHN5Dx4CdVovBGoGAu2AqdiN2TExC1S1ZIVA0521tyt68BCo03ohUDMQaDj4LdDKe6BlAtXugSrHVoSlpTcy9ZadLgTqsF4I1EzcApVbdqZVm8sFkzjJb4ESLzKxiYF03krk4+/lAuVi5KPwO+K2Jru9uTws68Pf0oyaO10I1GG9EKiZ6AUqtQmBWtFAoGzCZnpvnfqNaPH4bTqvs0qga9/I5oGSY0/cZuuUNqrC0oPXnq1YRRqnQNWNf/qsFwI1w36xBhcoOIFKt0GgVjQQqFwyxGQ5449fuLZcoHIlEmuqypVIp9LKsCzw8h58nAKVW0/2XS8EWgP6izW5QOEJVHTiIVArmghUWQtPHr9GHx9WCJSvhT8lZiSxtfB89XtVWLpmaXkPPkqBZpuf91wvBFqTRhcoNIGe/qdET5H56GYi8xIvCoWR+9gjgQ6HtHA5EQp0kX6n33pTCLQezS5QcAL9zze0TEdiN5DNwr6eAeQ+hkBTZfpTKR5n5bQl0PSOOYLKyrmgfu7Nugz9GxkoycopRuKzTee27qaf30wUawWT+xgCJT39ikmgKQTqLRBoGBexLK0xl5zc9pjraqKsFAom9zEEujOqHEJCF95hvSm68PVodoGC68J/RH1FVKUn3lDbfcHkPoZAd8VuzEuJUKAYRDKVxCBStwLlrUA99Zs68h5M7mMI1EiMAsU0JkPJoQUa9TQmpi/a7RYGE95Ut+sMJvcxBGokSoFiIn11ycEFGvNEeqYv2on/fX8t0K5yH0OgRuIUKJZyVpYcfCJ9zEs5ub5IJ/6vjfdAvc99DIEagUBd1guBmlkNgbL5l8ooPDFZcRTe+9zHEKgRCNRlvRComRURKJu3aZgH6n3uYwjUCATqsl4I1MyKCDTbl6liJZL3uY8hUCMQqMt6IVAzqyJQOQE+ffQmEdgrZWvhvc99DIEagUBd1guBmolboJ7TMPcxBGoEAnVZLwRqBgIdkIa5jwcRaGg8Bfwk910GnjKAZGxpmvsYAq3B0N8/sITcdxl4ygCSsaN57uNwfjcAAOiU5rmPIVAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAE29nVYOjdwMASct9l4CkDSKYvsCO9EexI77Je7EhvBjvShwMEagQCdVkvBGoGAg0HCNQIBOqyXgjUDAQaDhCoEQjUZb0QqBkINBwgUCMQqMt6IVAzEGg4QKBGIFCX9UKgZiBQwVGz/ERDAIEagUBd1guBmlkNgU6L+S8Pxqc/Up7ev3y1qs6SAP0DgRqBQF3WC4GagUAZRzcSCLQMCFQ/tPGxPyUMUK16sA/V+ifQxYVpHzZ6gZbQTKBeAIEa8U6gP/1p9ocKgarPmx1eWdJKoMqFaR8WAoVAlwCB6oc2PPanP138oUKg6vNmh1eWtBGoemHah41WoPPk/HycnHlX9MA/vzNOknP7EypLKtBPX0qSM++ktIdOkQqVNp0kW/ssyNY+C3Aw3vrDh2NxSC5cH0CgRjwT6E9/qvyhQqDq82aHV5a0EKh2YdqHjVigXyOOO/0RF+jBmHnyzLeEQL+VSG/qAiVPz6fMo5vvimdCoGcu80Po23q4PoBAjTzzzB+d89Nhcf8LDUFBoI7j42q44SmxJ4+4TPMk2bqb/o77jwjxzN306AOuSqq/V/fTRzdYM1PvwpOm5j4vcZW+RTQqBCoPob1/PVwfQKBGIFBPgUDDoCBQ1obk/psn/K7nVApUtCNpEV2gT7ZpyXnyd7QIs6kUqHKIHq4PIFAj6MKXHOxDtejChxG20IWXkjtLb2ky/RE9coFytz7ZLgo0Zbc1J5s/pO6c02OFQNVD9HB9EJBAD/cc1d8wkGcCxSCSxDOBYhBpCQWBsmEg5r+FI7NBJPqkVKBzVn7r97QlOuE3Sc/mDsmF6wMvBfpg/en3Cy/eu3jJdNzjCyPBc28tL1UjkIZvAnU0jQkT6atKDjqNKe6J9LpAefuxQqBzOar0ZHtr/2B8ljRC3+Xd+TKBauH6IBiBHl4bNRDoaHRyWaE6gTS8E6ibifQQaFXJQSfSr5JAjS3QTKDUnHPyc5qcZz14tECXYi9Qcdzhz9dHG0sKRSBQJ9VCoFUl7QTqKOzqCDS7acnVV9mFJwdcJQ6lXfkpe6Mo0Fy4PohToGm6Ozqx5E4nBMqBQKtKQqD9CFSOKM0Ts0APxn9FevHkzTOXxVzQgkD1cH3gsUAfrJ/45Mfro9Fxej9zl/XLL6Wz0cZsfXT87TS99xp54djrqiYVgQoHK4XEkX/LA5Hg/MidpU3V7HQhUIf1QqBmVkigYuLmr8flAv2OeiB5Lg7hEUoEqofrA68Fevwiv5+5oQr0y8Sp5O33xL1OtaFZEKhaSBz5DzzQ4bW1t/kh/GfV6UKgDuuFQM2skEDl0qGtHxQFSjoVuAg9AAAW3UlEQVTkYn2RQMzunIhXSwSqh+sDrwU6Gr2wlz68Rn0pe94zYsPb6a/Iz7U3yIvvjdT+eL4LrxWSR4pAu7zlOVva1V+cLgTqsF4I1MwqCZQtXt9U1sLT14QNj24m2o51Ygq+NhM/d4gWrg/8FugGf0YbiZlAeYtR9LzJqxuL4zKBfnaLOVMrJI8UgUQf3tyDh0Cd1guBmolboKU4HvXBINL7Upyyl50JVBtfygt0MY3pVL6QPFIE4n34Gj34WAWKifRVJQcVaMOovoetEqjcFDm3F70tjsPVwGuBcuPlBJp1uQ9/8ZPvPTsqFeix5/+1UEgeKUfhd9UXK08XAnVYLwTqPKrvYasEOmdbgaT3x252l3ccrgbBCvTjZ0dyhGk2EiNMyj3QNF+oINDHF8jzGj14CNRpvRCo86i+h60SKB1S58M+TvLHOQ5Xg1AFSqS59tzXv//La1UCVQsVBJrurL1dpwcPgTqtFwJ1HtX3sNX3QO+/SXz31SuuhOc4nJFABSrvfS4ZROLohQoCpRNDl6/4VE4XAnVYLwTqPKrvYW2HKwNIahysQKUqZ+sVAtULFQRK+vC36ixKgkBd1guBOo/qe1hLgRqSGntCSAL9RqoIdHRyLz2kC5U2FscVBKoWUgT6Df7+ztqzJbs+FU8XAnVYLwTqPKrvYe0EGkRKuYAEmu6IASOuwV2xxOiW2gnP3wPVCmXDTzxQym6R1ujBRy1Q0/ZB7uuFQB1FVS4dBDoc4Qj08Dr1nTYKf+wNfR5S6Si8LJSV5IFY8VrbikQqUPq1Nm5g6b5eCNRMnYn06qWDQIfDS4H2RMG35cQrUPMW6u7rhUDN1BCodulCE+j9y0ny4hX++NHNcZK8fJc+1DIUL3JyKiVkRuT659U5qyzQWmPwEQu0RhIf9/VCoGbMAtUvXWACnSppiOfjbL9kPUNxJlC1hMyIXP+8OmeFBfqwziTQtJusnI5ongGyC4b67bvOytkfcV+uXFbOg3Hy6v7RB8yDT7aTc/s0DTHdCaSQoZg6UyshMyJ7xMoKdKcq7YcGBGpgqN8eAg3jcuUEytercz/KteslGYqFQLUSch8mj1hZge6ORqfqZedEF95lvejCm4m6C68ODmVJ4Fie97KkxnqJuV/dd8rKCrQ+0QoUg0jLS3ou0IAHkeTGnfxxIiFmLEvooZeY97fGvS4QqJF4BYppTEtL+i7QcKcxQaCtgUD1QzGR3q7aaAVaK6py6QIWqHpPs1ygagkIlNGtQA/r3dmsT8wC7b9eCNR5VN/DVt0DVSfLlwlULwGBMpoJdLHN/HNvVRbcZaPq9y5eyh67AQJ1WS8E6jyq72Fz12nCx9VFWnhuRGbG0qTGWgkIlGErUMO8IybNLGUcBNphtRBo92GjFSibB0o3jWdZ5OjEzvRTNoGpNKmxVgICZTQVqFhwefjzdfP+8dlmde6AQF3WC4E6j+p72CUrkVg7VK4zOpcuS2qsloBAGZYCFbmKq4FA+6gWAu0+bLwCLa6FZ6vflyU1VkpAoAxrgYr9mR5epzdEb7OX+GN2c5R223dFcg/RhVdKPlg/8QndGfR49Y3UstOFQB3WC4E6j+p72FYJtH0nQIHO1pkl13h29yxpXIlA9ZLHLy7KNjpdCNRhvRCo86i+h4VAHdOuC0+ceeJ2+tn1Ed0KZIftOX+LpXwvDCJpJalqX9hLH14b1drDTj3dOAXa6msNgXYZts5EeouwvGz/YSFQx1gK9LNbtG1JnMlvhBJ3ZnstM2sWBKqWpALdoE8erNfbg0k5XQjUYb0QqBkINBxCEOhiGtMpLanmiT3yZHFPMy9QrWQmzlqZjPXThUAd1guBmlldgQaRiFMjIIEee/5fU0WA7IYoSwl/7HWRJkkXqF4ylyCkyelCoA7rhUDNxC1QfXWm4NfjJPnKviERp9zazidCEGhprmLx4B4fGXp+r0ygakkINAcEWlUSAu1VoHM2MdSUBgkC5bQUqNquJBz+y2t8jRJaoE2w3Uakbb0QqJlqgRavXPgCnZLmZzB55DSCE6h+Z1OwS4fWTfdAIVAF643sWtYLgdagUqAlVy58gU7YXvQQaD1aCVSOrRM9nsysyH4uG4VnJSFQDfutlNvVC4HWoUqgZVcuTIEusm3O+X6f/5Qlj6NIm4rdROgiJJH4Q8ndSfj8Dnlybn8ykHvDE6g6u5O4kTymkzuVLvw30vJ5oBBoRotkHq3qTSHQllFLr1yQAlWybZYKlHTrRauUFafPhECV3J08Ex3hzLcg0CUUsreXrUTKJtKzZHEbpSuR7AXaexqurhkww5hDQk8qVz8PnCuG+T1zSeW4QLVsm6VdeJYFiQlS5kaSqef03J1n7tIwCQS6hIJA04d01Oh5uRaeSHKNzWPi0jy8PmJLOk/mSkKgCkP/SbkBAg1YoFq2zVKBPtmmhpwnf8e3uiM2LcndKdPMTSFQb0EX3lm9KbrwLaOWXrkAu/B6ts3yQSR2W3Oy+UOej/NslvxYzd3JD2QNWgjUUyIUKAaRTCV9FWgsg0h6srhygVJpHt3Y+j1tiU6yLPLapneLIzCI5C0xChTTmAwlvRVoJNOYKgQ6l4NLT7a39g/GZ0kj9F3enS8TqJwSBYF6S5QCxUT66pL+CjSOifS5yaClAqXmnJOf0+Q868GjBSqAQPVDBxEo9gOtLOmxQIMLW34PNHe7s2wi/TS5ShxKu/JT9kZRoNk90MHm4EOgRiIVKNbCV5X0diJ9i7C8bP9hS+eBatk2lwj0YPxXpBdPDjhzWcwFLQhUjsLPMQrvLRCoy3ohUDOrIFAt2+ZCoN9RS5LnVJn0B7NtiUDFPNBfjyFQb4FAXdYLgZpZBYFq2TZlT3wi1xcJxOzOiXi1RKByJdLWDyBQX4FAXdYLgZpZCYGq2TalQGUiTsmcr1MSP0oFytbCb2ItvMdAoC7rhUDNxC3QTsAgkr9AoC7rhUDNQKC1kStCZbu0dyBQIxCoy3ohUDMQaG3mbGeR9P54qM3qBxFoaDwF/CT3XQae0p1L6Ag9H0UaKB0dBFqDob9/YAm57zLwlC5tcv9Nos+vXhkqnWfMKZsBAKBTIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAEAgUAAEsgUAAAsAQCBQAASyBQAACwBAIFAABLIFAAALAE29nVYOjdwMASct9l4CkDSKYvsCO9EexI77Je7EhvBjvShwMEaiRSgTo02UDVRivQhlF9DwuBOgYC1Q+FQO2qhUDDCAuBOgYC1Q+FQO2qhUDDCAuBOqatQB+sjzh/+fqeqezjC2tvt6wOAnVZLwTqPKrvYSFQxzgT6GhktCME2kW1EGj3YWMV6CTZfFc+niqPAyVMgT79Pv15+IuLRoNCoF1UC4F2HzZWgT7ZzlIQH4yTq/Wr8JOQBUoUem10srosBGqu9s+E3uqFQOtHrXthghIo1eZ59uDoRnK2fg2eErZAyUPqR/mCtOW910jv/hi7QQqBGqv985+bGxQC7TzsH+tfmLAEmnXcp8npj+rX4CmBCzTdGW0UBPqeuEF6Yg8CXY78Wv/5zxYGhUC7DMsn0te/MIEJlLQ8aSd+0YF/dHOcJC/fFY8T8vid+jUPTOgC3aV9eF2gs9HaG6R3TzR6CQJdjvha//nPNgaFQLsMy36xBhcmMIGKTvxEduDnRJ+Uq/wtxvn6VQ9L6AKd0XamLlDWKGX3RzccCfSPofDnfhn4ty0IdODzqU90l6KSp8SWEosrRTvvc9mBf7KdnNtPjz5gHXtiVfY4mM59hAIVQKCdM/BvC4F6cykqKQqUdOL/alt24KeiJUp/Ptlmt0fJ+6EMz4cv0EIXPqUTnH7yvWdHzgRaoxC68HWPRBfeSOxdeN5TFx34oxtiLujBeGufmPNMOPc/KaELtOQeaPrxs2IUaQMCXQ4GkapKDi/QeAeRKIsReNKDl5CX5vTni9/er1/zwIQu0JJR+NlotPbc17//S3dd+BqFwhUopjGVlfRAoNFOY6LMs9n0ukDT+5fZw1dCUWjgAi2ZB8rvfTq9B1qjUMACxUT6kpI+CDTSifQMVaC55ZxH//ZmkgQzxT5sgYqVSFyjtD9Pfj6+wN+drUOgXVULgXYfdgDTdRS2WqClA0bhzLEPWaCH9y6O2CPi0eO308NbIy7Q0cm99PDH67gH2lm1EGj3YVdFoOlEPKQvHYy5OOVP/wlToPndmGb82QvX6PNdsQ7pFm2dQqBdVAuBdh92ZQR6ME627qbpp3R2PV2kRB4/CmeVfNACfe4tuR8oXf1+7I3Da9ko/LE3+BRRCLSLaiHQ7sOujECzlUjn0sVKpFAaoEEKtGcgUJf1QqDOo/oe1iRQvhZezP9kjzfDmccEgRqBQF3WC4E6j+p7WOxI7xgIVD8UArWrFgINIywE6hgIVD8UArWrFgINIywE6hgIVD90GIG2+lpDoF2GlRPpHYflZfsPC4E6BgLVD4VA7aqFQJuF5WX7DwuBOgYC1Q+FQO2qhUCbheVl+w8LgToGAtUPhUDtqoVAm4XlZfsPuyypXMk6+PCAQI1AoC7rhUDNRC9QqU0I1Io6QvrF9fXRaO3527WD7tAMSLtalmP2UnviFKjFFkxO6oVAl7G4ItELVM6ih0CtMAvp4cXRYk/kekCgjbDZBNRFvRDoMpQrEr9ARSceArXCKKTHF0bH6TL3h9frG7TElhDoUqy2oXdQLwS6DPWKxC7Q0/8kOvFSoDyX8d361fmDjwI9vMZSulN2R4vN56uBQBtglwipfb0pBLqE4hWJWaD/mWeGlwIVu4lshpJITsVHgc4W1pTby9PdlkbHXqdafbB+4hO62efxt3iRz94jT07tqV149SXtWPLkItupiYXhr+yYGrkBZeWsSxjZHE0Ek5WzfnLNWgz96zQll5WT7vUpRuK5QPl+dp/fTELsz/soUFVpnzHLvSfuiFLnPVg/flG5Pyr2tjv+NwuBai9px8q9Qjeomvk+d+b97iBQT4FAw6BEoOmU2ZILVO6oPAlmE1AFDwVKWp25rvdstEYajYdEhZe4Hl/YSx9eY+1UeruUb0afCVR/KX/sC3vkHXrkLhfwLLtdsPR00YV3VW+KLvwSilck5i78R2zn5H0u0Cynh7bFXSh4KNBim3BHTRP3YF02PXkKTu6/2UKg+kvasbyFyg0t+vDGHnyMAsUgkqnkoINIDaOGKFA+nZ4JNBuKDyePh0IQAhVIgap9b+k/0uyUAtVfUo/V2ra8D19jx/oYBYppTIaSg05jahg1SIGyTrwQqPBm9iAkQhHo4S9+8r1nR4Uk8AslZoNIuZfUY/XIrA9v7sHHKVBMpK8uOehE+oZRwxQo7cT/Hi1QGxrfA2VZjuToT06gUomKQLWX1GN1gT6+QNxp7sFHKlDsB1pZcgCBWkf1PWy5QGkn/q9xD9SGJqPws9Hze/Ru5tpzX//+L69ZtEDVY3Nt2521t+vknItUoFgLX1VyUIFGP5GeNzSndO7nYhT+KJxUnAo+ClQqkrLDlbhBHx8WBZrJlmtTuwfKXtKOzbVtZ6ONmbb2c8npQqAO64VAzayIQIkxE8wDtaDBSqSPaeb3xxe4MmfrRYHKSffaKLzykn7sDvelmG9P+vC3aixWgkBd1guBmlkRgWb7MmElUjOMQnqwPjr2xmIt/OMLo5N76SFdfrSRFyiRLZ30+fP1hUC1l/LH0imk99aFNnfWnq2xUhQCdVkvBGpmVQQqptOn6aM3iT9fwVr4mpiF9CDbjekUfSrWD5H24sm8QNOHF/h7312sRMq9pBwrn4l++2xUowcPgTqtFwI1E7dA48JPgaaHbAF7th8oHUk/9gafc5QTaHpYXAuvvqQdq6yF5yHqbDcCgbqsFwI1A4GGg6cC7Qd5g7QaCNRlvRCoGQg0HAYRqC/8T6P/vla5p4Cf5L7LwFMGkExfrLJA/8P/8N/9j7UKdvvtGkjQMVSb+y67o6MPZ1XDDiCZvoj5dwuEWrcIUG2vdHSWCBsdEOjgrJbJwvirDEtJYYWNCwh0cFbLZGH8VYalpLDCxgUEOjirZbIw/irDUlJYYeMCAh2c1TJZGH+VYSkprLBxAYEOzmqZLIy/yrCUFFbYuIBAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUD759HNYgYY9bUn2yzHVpKljum+ytIC3VfbwW/ahOrTo0kjk8X51T/XJZ/lk+2zZQVqf/LGsPffTJLNxp+sKaweqZvvScBAoL0jvpFaDlfttYOxa60Yqywr0EO17n9Th6eXE2jtc132WU6SsyUFan/yxrB3EiW3pbuz1SJ18z0JGQi0b8jf5dbd9BH5d3/Ja3P53e2tyrICPVTr/jd1e3qcgzHPvVvzXJd8lkeTRASw++SNYefJ5pWUFmCmc3a2WqRuvidBA4H2jcjqSv4vv7rktUlyvucqywr0UK3737QJ5tNjEGmwk6x7ruWf5aPLiVSS3SdvCitPs+EnazxbLVI335OggUD7Ziq+mVPli6m9dnTDdQ/JWGVZgR6qdf+bNsF4evIl1tyqfa6ln+U8Sc59mr1h88mbwj7ZFuc3afTJGs9Wi9TN9yRoINC+mYj/vedKP0h77cn26R+SFsAZd24xVllWoIdq3f+mTk+PIVtbtc+19LOcn3kn6wvbffLGsIuC512erRapm+9J0ECgPUO6WvxLeDDOvoT6a/KuvbP/5Y1VlhXooVr3v6nb02NMhCvqnuvyz3Ke9bUtPnljWAlviTo7Wy1SN9+TsIFAeybraon7ScXXSAdq6276+U1nY53GKssK9FCt+9/U7enxV7JGV71zXf5ZznN97UafvDGshN9xcHa2WqRuvidhA4H2jPnvVtx0W0wk6bzKoQTq/Dd1e3oUeYq1z3Vggc65Mp2drRYJAi0CgfZMvb9birMbTd4KVDLILbVapyfHtheYznVYgc7Hm1f1N1uerRYJAi0CgfbEnN9Julrz1lvq8Fvq7T1QySB/j7VOr3hmpnMd9B7oNN9lb322WiTcAy0CgfaEFGjNwd/UpVZ8HYWXDNOgqXN600IX2HiuSz/LDkbh1bDEhncKtzzbn60WCaPwBSDQvjFNP8z+m3f3LfV0HmgHv6nL06Nks8jrn+vSz3JxV9HZPFA1LD3FMx+5Pls9EuaBFoBA+8a4AGaiLy3po8qBViK5/02dnp5yi7DBuS79LBcTg9ytRFLCHk20lrSrs9UiYSVSAQi0b2hDoWQJ9uK1g3Fybp+upnPWrzVWWVagh2rd/6ZOT0/rAdc+16WfZWY6q0/eGHaq3xRxdbZapG6+J0EDgfaOmJq8KdZ2nC28Nk1cb3ljrFJ70l+17n9Tp6en9YBrn2tZWB7sbEmB2p+8IazcdU4sYnd3tlqkbr4nIQOB9o+6p6L8yupbRNKNHc+5/E/eXGXn+4H29Js6PT3tFmLtcy0Lm6rDMu33Ay2GnWf+5M8dnq0aCfuB5oBAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAALIFAAQDAEggUAAAsgUABAMASCBQAACyBQAEAwBIIFAAA/ls7dSwAAAAAMMjfeg67C6JJoACTQAEmgQJMAgWYBAowCRRgEijAFMcSG8j4Law8AAAAAElFTkSuQmCC" 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<pre><code>
[[6]]</code></pre>
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<figure class="figure">
<p><img 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" 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<pre><code>
[[7]]</code></pre>
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<figure class="figure">
<p><img 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</figure>
</div>
</div>
</div>
</section>
<section id="session-info" class="level2" data-number="14">
<h2 data-number="14" class="anchored" data-anchor-id="session-info"><span class="header-section-number">14</span> Session info</h2>
<div class="cell">
<details class="code-fold">
<summary>Code</summary>
<div class="sourceCode cell-code" id="cb165"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb165-1"><a href="#cb165-1" aria-hidden="true" tabindex="-1"></a><span class="fu">sessionInfo</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=German_Germany.utf8  LC_CTYPE=German_Germany.utf8   
[3] LC_MONETARY=German_Germany.utf8 LC_NUMERIC=C                   
[5] LC_TIME=German_Germany.utf8    

time zone: Europe/Berlin
tzcode source: internal

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] stargazer_5.2.3   ggridges_0.5.6    texreg_1.39.3     rio_1.1.1        
 [5] fastDummies_1.7.4 data.table_1.15.4 ggh4x_0.2.8       scales_1.3.0     
 [9] MASS_7.3-60.2     nnet_7.3-19       MNLpred_0.0.8     margins_0.3.28   
[13] cregg_0.4.0       haven_2.5.4       rvest_1.0.4       cjoint_2.1.1     
[17] survey_4.4-2      survival_3.6-4    Matrix_1.7-0      lmtest_0.9-40    
[21] zoo_1.8-12        sandwich_3.1-0    lubridate_1.9.3   forcats_1.0.0    
[25] stringr_1.5.1     dplyr_1.1.4       purrr_1.0.2       readr_2.1.5      
[29] tidyr_1.3.1       tibble_3.2.1      ggplot2_3.5.1     tidyverse_2.0.0  

loaded via a namespace (and not attached):
 [1] gtable_0.3.5      prediction_0.3.18 xfun_0.45         htmlwidgets_1.6.4
 [5] lattice_0.22-6    tzdb_0.4.0        vctrs_0.6.5       tools_4.4.1      
 [9] generics_0.1.3    fansi_1.0.6       pkgconfig_2.0.3   lifecycle_1.0.4  
[13] compiler_4.4.1    munsell_0.5.1     ggstance_0.3.7    mitools_2.4      
[17] httpuv_1.6.15     htmltools_0.5.8.1 yaml_2.3.8        pillar_1.9.0     
[21] later_1.3.2       mime_0.12         tidyselect_1.2.1  digest_0.6.35    
[25] stringi_1.8.4     splines_4.4.1     fastmap_1.2.0     colorspace_2.1-0 
[29] cli_3.6.3         magrittr_2.0.3    utf8_1.2.4        withr_3.0.0      
[33] promises_1.3.0    timechange_0.3.0  rmarkdown_2.27    httr_1.4.7       
[37] hms_1.1.3         shiny_1.8.1.1     evaluate_0.24.0   knitr_1.47       
[41] rlang_1.1.4       Rcpp_1.0.12       xtable_1.8-4      glue_1.7.0       
[45] DBI_1.2.3         xml2_1.3.6        rstudioapi_0.16.0 jsonlite_1.8.8   
[49] R6_2.5.1         </code></pre>
</div>
</div>
</section>

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});
</script>
</div> <!-- /content -->




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